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Computer vision is an interdisciplinary scientific field that deals with how
computer A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations (computation) automatically. Modern digital electronic computers can perform generic sets of operations known as Computer program, pr ...
s can gain high-level understanding from
digital image A digital image is an image composed of picture elements, also known as ''pixels'', each with '' finite'', '' discrete quantities'' of numeric representation for its intensity or gray level that is an output from its two-dimensional function ...
s or
video Video is an electronic medium for the recording, copying, playback, broadcasting, and display of moving visual media. Video was first developed for mechanical television systems, which were quickly replaced by cathode-ray tube (CRT) ...
s. From the perspective of
engineering Engineering is the use of scientific principles to design and build machines, structures, and other items, including bridges, tunnels, roads, vehicles, and buildings. The discipline of engineering encompasses a broad range of more specializ ...
, it seeks to understand and automate tasks that the human visual system can do. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory. The
scientific discipline The branches of science, also referred to as Science, sciences, scientific fields or scientific disciplines, are commonly divided into three major groups: *Formal sciences: the study of formal systems, such as those under the branches of logic ...
of computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras, multi-dimensional data from a 3D scanner, or medical scanning devices. The technological discipline of computer vision seeks to apply its theories and models to the construction of computer vision systems. Sub-domains of computer vision include scene reconstruction,
object detection Object detection is a computer technology related to computer vision Computer vision is an Interdisciplinarity, interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From ...
, event detection, video tracking,
object recognition Object recognition – technology in the field of computer vision Computer vision is an Interdisciplinarity, interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. ...
, 3D pose estimation, learning, indexing,
motion estimation Motion estimation is the process of determining ''motion vectors'' that describe the transformation from one 2D image to another; usually from adjacent video frame, frames in a video sequence. It is an well-posed problem, ill-posed problem as the ...
, visual servoing, 3D scene modeling, and
image restoration Image restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image. Corruption may come in many forms such as motion blur Motion blur is the apparent streaking of moving objects in a photograph or a sequ ...
.


Definition

Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from
digital image A digital image is an image composed of picture elements, also known as ''pixels'', each with '' finite'', '' discrete quantities'' of numeric representation for its intensity or gray level that is an output from its two-dimensional function ...
s or
video Video is an electronic medium for the recording, copying, playback, broadcasting, and display of moving visual media. Video was first developed for mechanical television systems, which were quickly replaced by cathode-ray tube (CRT) ...
s. From the perspective of
engineering Engineering is the use of scientific principles to design and build machines, structures, and other items, including bridges, tunnels, roads, vehicles, and buildings. The discipline of engineering encompasses a broad range of more specializ ...
, it seeks to automate tasks that the human visual system can do. "Computer vision is concerned with the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images. It involves the development of a theoretical and algorithmic basis to achieve automatic visual understanding."http://www.bmva.org/visionoverview The British Machine Vision Association and Society for Pattern Recognition Retrieved February 20, 2017 As a
scientific discipline The branches of science, also referred to as Science, sciences, scientific fields or scientific disciplines, are commonly divided into three major groups: *Formal sciences: the study of formal systems, such as those under the branches of logic ...
, computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply its theories and models for the construction of computer vision systems.


History

In the late 1960s, computer vision began at universities that were pioneering
artificial intelligence Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animal cognition, animals and human intelligence, humans. Example tasks in ...
. It was meant to mimic the human visual system, as a stepping stone to endowing robots with intelligent behavior. In 1966, it was believed that this could be achieved through a summer project, by attaching a camera to a computer and having it "describe what it saw". What distinguished computer vision from the prevalent field of
digital image processing Digital image processing is the use of a digital computer to process digital images through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows ...
at that time was a desire to extract
three-dimensional Three-dimensional space (also: 3D space, 3-space or, rarely, tri-dimensional space) is a geometric setting in which three values (called ''parameters'') are required to determine the position (geometry), position of an element (i.e., Point (m ...
structure from images with the goal of achieving full scene understanding. Studies in the 1970s formed the early foundations for many of the computer vision
algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algorithms are used as specificat ...
s that exist today, including extraction of edges from images, labeling of lines, non-polyhedral and polyhedral modeling, representation of objects as interconnections of smaller structures,
optical flow Optical flow or optic flow is the pattern of apparent motion (physics), motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer and a scene. Optical flow can also be defined as the distribution o ...
, and
motion estimation Motion estimation is the process of determining ''motion vectors'' that describe the transformation from one 2D image to another; usually from adjacent video frame, frames in a video sequence. It is an well-posed problem, ill-posed problem as the ...
. The next decade saw studies based on more rigorous mathematical analysis and quantitative aspects of computer vision. These include the concept of scale-space, the inference of shape from various cues such as
shading Shading refers to the depiction of depth perception in 3D models (within the field of 3D computer graphics) or illustrations (in visual art) by varying the level of darkness. Shading tries to approximate local behavior of light on the object's ...
, texture and focus, and contour models known as snakes. Researchers also realized that many of these mathematical concepts could be treated within the same optimization framework as regularization and
Markov random field In the domain of physics Physics is the natural science that studies matter, its Elementary particle, fundamental constituents, its motion and behavior through Spacetime, space and time, and the related entities of energy and force. "Phy ...
s. By the 1990s, some of the previous research topics became more active than others. Research in projective 3-D reconstructions led to better understanding of camera calibration. With the advent of optimization methods for camera calibration, it was realized that a lot of the ideas were already explored in bundle adjustment theory from the field of
photogrammetry Photogrammetry is the science and technology of obtaining reliable information about physical objects and the environment through the process of recording, measuring and interpreting photographic images and patterns of electromagnetic radiant ima ...
. This led to methods for sparse 3-D reconstructions of scenes from multiple images. Progress was made on the dense stereo correspondence problem and further multi-view stereo techniques. At the same time, variations of graph cut were used to solve
image segmentation In digital image processing Digital image processing is the use of a digital computer to process digital images through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over ana ...
. This decade also marked the first time statistical learning techniques were used in practice to recognize faces in images (see
Eigenface An eigenface () is the name given to a set of eigenvectors when used in the computer vision problem of human facial recognition system, face recognition. The approach of using eigenfaces for Facial recognition system, recognition was developed by ...
). Toward the end of the 1990s, a significant change came about with the increased interaction between the fields of
computer graphics Computer graphics deals with generating images with the aid of computers. Today, computer graphics is a core technology in digital photography, film, video games, cell phone and computer displays, and many specialized applications. A great deal ...
and computer vision. This included image-based rendering, image morphing, view interpolation, panoramic image stitching and early light-field rendering. Recent work has seen the resurgence of
feature Feature may refer to: Computing * Feature (CAD), could be a hole, pocket, or notch * Feature (computer vision), could be an edge, corner or blob * Feature (software design) is an intentional distinguishing characteristic of a software item ...
-based methods, used in conjunction with machine learning techniques and complex optimization frameworks. The advancement of Deep Learning techniques has brought further life to the field of computer vision. The accuracy of deep learning algorithms on several benchmark computer vision data sets for tasks ranging from classification, segmentation and optical flow has surpassed prior methods.


Related fields


Solid-state physics

Solid-state physics Solid-state physics is the study of rigid matter, or solids, through methods such as quantum mechanics, crystallography, electromagnetism, and metallurgy. It is the largest branch of condensed matter physics. Solid-state physics studies how the l ...
is another field that is closely related to computer vision. Most computer vision systems rely on
image sensors An image sensor or imager is a sensor that detects and conveys information used to make an image. It does so by converting the variable attenuation of light waves (as they refraction, pass through or reflection (physics), reflect off objects) in ...
, which detect
electromagnetic radiation In physics, electromagnetic radiation (EMR) consists of waves of the electromagnetic field, electromagnetic (EM) field, which propagate through space and carry momentum and electromagnetic radiant energy. It includes radio waves, microwaves, inf ...
, which is typically in the form of either visible or
infrared light Infrared (IR), sometimes called infrared light, is electromagnetic radiation (EMR) with wavelengths longer than those of Light, visible light. It is therefore invisible to the human eye. IR is generally understood to encompass wavelengths from ...
. The sensors are designed using
quantum physics Quantum mechanics is a fundamental Scientific theory, theory in physics that provides a description of the physical properties of nature at the scale of atoms and subatomic particles. It is the foundation of all quantum physics including qua ...
. The process by which light interacts with surfaces is explained using physics. Physics explains the behavior of
optics Optics is the branch of physics that studies the behaviour and properties of light, including its interactions with matter and the construction of optical instruments, instruments that use or Photodetector, detect it. Optics usually describes t ...
which are a core part of most imaging systems. Sophisticated
image sensors An image sensor or imager is a sensor that detects and conveys information used to make an image. It does so by converting the variable attenuation of light waves (as they refraction, pass through or reflection (physics), reflect off objects) in ...
even require
quantum mechanics Quantum mechanics is a fundamental Scientific theory, theory in physics that provides a description of the physical properties of nature at the scale of atoms and subatomic particles. It is the foundation of all quantum physics including qua ...
to provide a complete understanding of the image formation process. Also, various measurement problems in physics can be addressed using computer vision, for example, motion in fluids.


Neurobiology

Neurobiology Neuroscience is the scientific study of the nervous system In Biology, biology, the nervous system is the Complex system, highly complex part of an animal that coordinates its Behavior, actions and Sense, sensory information by transmit ...
has greatly influenced the development of computer vision algorithms. Over the last century, there has been an extensive study of eyes, neurons, and brain structures devoted to the processing visual stimuli in both humans and various animals. This has led to a coarse, yet convoluted, description of how natural vision systems operate in order to solve certain vision-related tasks. These results have led to a sub-field within computer vision where artificial systems are designed to mimic the processing and behavior of biological systems at different levels of complexity. Also, some of the learning-based methods developed within computer vision (''e.g.''
neural net Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units ...
and
deep learning Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be Supervised learning, supervised, Semi-supervised l ...
based image and feature analysis and classification) have their background in neurobiology. The Neocognitron, a neural network developed in the 1970s by Kunihiko Fukushima, is an early example of computer vision taking direct inspiration from neurobiology, specifically the
primary visual cortex The visual cortex of the brain is the area of the cerebral cortex that processes visual perception, visual information. It is located in the occipital lobe. Sensory input originating from the eyes travels through the lateral geniculate nucleus in ...
. Some strands of computer vision research are closely related to the study of biological vision—indeed, just as many strands of AI research are closely tied with research into human intelligence, and the use of stored knowledge to interpret, integrate and utilize visual information. The field of biological vision studies and models the physiological processes behind visual perception in humans and other animals. Computer vision, on the other hand, develops and describes the algorithms implemented in software and hardware behind artificial vision systems. An interdisciplinary exchange between biological and computer vision has proven fruitful for both fields.


Signal processing

Yet another field related to computer vision is
signal processing Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing '' signals'', such as sound In physics, sound is a vibration that propagates as an acoustic wave, through a transmission med ...
. Many methods for processing of one-variable signals, typically temporal signals, can be extended in a natural way to the processing of two-variable signals or multi-variable signals in computer vision. However, because of the specific nature of images, there are many methods developed within computer vision that have no counterpart in the processing of one-variable signals. Together with the multi-dimensionality of the signal, this defines a subfield in signal processing as a part of computer vision.


Robotic navigation

Robot navigation Robot localization denotes the robot's ability to establish its own position and orientation within the frame of reference In physics Physics is the natural science that studies matter, its Elementary particle, fundamental constitu ...
sometimes deals with autonomous
path planning Motion planning, also path planning (also known as the navigation problem or the piano mover's problem) is a computational problem In theoretical computer science, a computational problem is a problem that may be solved by an algorithm. For e ...
or deliberation for robotic systems to navigate through an environment. A detailed understanding of these environments is required to navigate through them. Information about the environment could be provided by a computer vision system, acting as a vision sensor and providing high-level information about the environment and the robot.


Other fields

Besides the above-mentioned views on computer vision, many of the related research topics can also be studied from a purely mathematical point of view. For example, many methods in computer vision are based on
statistics Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of ...
,
optimization Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfi ...
or
geometry Geometry (; ) is, with arithmetic, one of the oldest branches of mathematics. It is concerned with properties of space such as the distance, shape, size, and relative position of figures. A mathematician who works in the field of geometry is ca ...
. Finally, a significant part of the field is devoted to the implementation aspect of computer vision; how existing methods can be realized in various combinations of software and hardware, or how these methods can be modified in order to gain processing speed without losing too much performance. Computer vision is also used in fashion eCommerce, inventory management, patent search, furniture, and the beauty industry.


Distinctions

The fields most closely related to computer vision are
image processing An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual system to convey information. An image can be an artifact, such as a photograph or other two-dimensiona ...
,
image analysis Image analysis or imagery analysis is the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques. Image analysis tasks can be as simple as reading barcode, bar coded tags or a ...
and
machine vision Machine vision (MV) is the technology and methods used to provide image, imaging-based automation, automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine ...
. There is a significant overlap in the range of techniques and applications that these cover. This implies that the basic techniques that are used and developed in these fields are similar, something which can be interpreted as there is only one field with different names. On the other hand, it appears to be necessary for research groups, scientific journals, conferences, and companies to present or market themselves as belonging specifically to one of these fields and, hence, various characterizations which distinguish each of the fields from the others have been presented. In image processing, the input is an image and the output is an image as well, whereas in computer vision, an image or a video is taken as an input and the output could be an enhanced image, an understanding of the content of an image or even behavior of a computer system based on such understanding.
Computer graphics Computer graphics deals with generating images with the aid of computers. Today, computer graphics is a core technology in digital photography, film, video games, cell phone and computer displays, and many specialized applications. A great deal ...
produces image data from 3D models, and computer vision often produces 3D models from image data. There is also a trend towards a combination of the two disciplines, ''e.g.'', as explored in
augmented reality Augmented reality (AR) is an interactive experience that combines the real world and computer-generated content. The content can span multiple sensory Modality (human–computer interaction), modalities, including visual, Hearing, auditory, hap ...
. The following characterizations appear relevant but should not be taken as universally accepted: *
Image processing An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual system to convey information. An image can be an artifact, such as a photograph or other two-dimensiona ...
and
image analysis Image analysis or imagery analysis is the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques. Image analysis tasks can be as simple as reading barcode, bar coded tags or a ...
tend to focus on 2D images, how to transform one image to another, ''e.g.'', by pixel-wise operations such as contrast enhancement, local operations such as edge extraction or noise removal, or geometrical transformations such as rotating the image. This characterization implies that image processing/analysis neither requires assumptions nor produces interpretations about the image content. * Computer vision includes 3D analysis from 2D images. This analyzes the 3D scene projected onto one or several images, ''e.g.'', how to reconstruct structure or other information about the 3D scene from one or several images. Computer vision often relies on more or less complex assumptions about the scene depicted in an image. *
Machine vision Machine vision (MV) is the technology and methods used to provide image, imaging-based automation, automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine ...
is the process of applying a range of technologies and methods to provide imaging-based automatic inspection, process control, and robot guidance in industrial applications. Machine vision tends to focus on applications, mainly in manufacturing, ''e.g.'', vision-based robots and systems for vision-based inspection, measurement, or picking (such as bin picking). This implies that image sensor technologies and control theory often are integrated with the processing of image data to control a robot and that real-time processing is emphasized by means of efficient implementations in hardware and software. It also implies that external conditions such as lighting can be and are often more controlled in machine vision than they are in general computer vision, which can enable the use of different algorithms. * There is also a field called
imaging Imaging is the representation or reproduction of an object's form; especially a visual representation (i.e., the formation of an image An image is a visual representation of something. It can be two-dimensional, three-dimensional, or som ...
which primarily focuses on the process of producing images, but sometimes also deals with the processing and analysis of images. For example,
medical imaging Medical imaging is the technique and process of imaging the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues (physiology). Medical imaging seeks to rev ...
includes substantial work on the analysis of image data in medical applications. * Finally,
pattern recognition Pattern recognition is the automated recognition of patterns and regularities in data. It has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer ...
is a field that uses various methods to extract information from signals in general, mainly based on statistical approaches and
artificial neural networks Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units ...
. A significant part of this field is devoted to applying these methods to image data.
Photogrammetry Photogrammetry is the science and technology of obtaining reliable information about physical objects and the environment through the process of recording, measuring and interpreting photographic images and patterns of electromagnetic radiant ima ...
also overlaps with computer vision, e.g., stereophotogrammetry vs.
computer stereo vision Computer stereo vision is the extraction of 3D information from digital images, such as those obtained by a CCD camera. By comparing information about a scene from two vantage points, 3D information can be extracted by examining the relative posit ...
.


Applications

Applications range from tasks such as industrial
machine vision Machine vision (MV) is the technology and methods used to provide image, imaging-based automation, automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine ...
systems which, say, inspect bottles speeding by on a production line, to research into artificial intelligence and computers or robots that can comprehend the world around them. The computer vision and machine vision fields have significant overlap. Computer vision covers the core technology of automated image analysis which is used in many fields. Machine vision usually refers to a process of combining automated image analysis with other methods and technologies to provide automated inspection and robot guidance in industrial applications. In many computer-vision applications, computers are pre-programmed to solve a particular task, but methods based on learning are now becoming increasingly common. Examples of applications of computer vision include systems for: * Automatic inspection, ''e.g.'', in manufacturing applications; * Assisting humans in identification tasks, e.g., a species identification system; * Controlling processes, ''e.g.'', an
industrial robot An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on three or more axes. Typical applications of robots include welding Welding is a fabrication process t ...
; * Detecting events, ''e.g.'', for visual surveillance or people counting, e.g., in the restaurant industry; * Interaction, ''e.g.'', as the input to a device for computer-human interaction; * Modeling objects or environments, ''e.g.'', medical image analysis or topographical modeling; * Navigation, ''e.g.'', by an
autonomous vehicle Vehicular automation involves the use of mechatronics, artificial intelligence, and multi-agent systems to assist the operator of a vehicle (car, aircraft, watercraft, or otherwise).Hu, J.; Bhowmick, P.; Lanzon, A.,Group Coordinated Control o ...
or mobile robot; * Organizing information, ''e.g.'', for indexing databases of images and image sequences. *Tracking surfaces or planes in 3D coordinates for allowing Augmented Reality experiences.


Medicine

One of the most prominent application fields is medical computer vision, or medical image processing, characterized by the extraction of information from image data to diagnose a patient. An example of this is the detection of
tumour A neoplasm () is a type of abnormal and excessive growth of tissue. The process that occurs to form or produce a neoplasm is called neoplasia. The growth of a neoplasm is uncoordinated with that of the normal surrounding tissue, and persists ...
s,
arteriosclerosis Arteriosclerosis is the thickening, hardening, and loss of elasticity of the walls of Artery, arteries. This process gradually restricts the blood flow to one's organs and tissues and can lead to severe health risks brought on by atherosclerosis ...
or other malign changes; measurements of organ dimensions, blood flow, etc. are another example. It also supports medical research by providing new information: ''e.g.'', about the structure of the brain, or the quality of medical treatments. Applications of computer vision in the medical area also include enhancement of images interpreted by humans—ultrasonic images or X-ray images, for example—to reduce the influence of noise.


Machine vision

A second application area in computer vision is in industry, sometimes called
machine vision Machine vision (MV) is the technology and methods used to provide image, imaging-based automation, automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine ...
, where information is extracted for the purpose of supporting a production process. One example is quality control where details or final products are being automatically inspected in order to find defects. One of the most prevalent fields for such inspection is the
Wafer A wafer is a crisp, often sweet, very thin, flat, light and dry biscuit A biscuit is a flour, flour-based baked and shaped food product. In most countries biscuits are typically hard, flat, and unleavened. They are usually sweet and may be ...
industry in which every single Wafer is being measured and inspected for inaccuracies or defects to prevent a
computer chip An integrated circuit or monolithic integrated circuit (also referred to as an IC, a chip, or a microchip) is a set of electronic circuit An electronic circuit is composed of individual electronic components, such as resistors, transistor ...
from coming to market in an unusable manner. Another example is a measurement of the position and orientation of details to be picked up by a robot arm. Machine vision is also heavily used in the agricultural processes to remove undesirable food stuff from bulk material, a process called optical sorting.


Military

Military applications are probably one of the largest areas of computer vision. The obvious examples are the detection of enemy soldiers or vehicles and
missile guidance Missile guidance refers to a variety of methods of guiding a missile or a guided bomb to its intended target. The missile's target accuracy is a critical factor for its effectiveness. Guidance systems improve missile accuracy by improving its ...
. More advanced systems for missile guidance send the missile to an area rather than a specific target, and target selection is made when the missile reaches the area based on locally acquired image data. Modern military concepts, such as "battlefield awareness", imply that various sensors, including image sensors, provide a rich set of information about a combat scene that can be used to support strategic decisions. In this case, automatic processing of the data is used to reduce complexity and to fuse information from multiple sensors to increase reliability.


Autonomous vehicles

One of the newer application areas is autonomous vehicles, which include
submersible A submersible is a small watercraft designed to operate underwater. The term "submersible" is often used to differentiate from other underwater vessels known as submarines, in that a submarine is a fully self-sufficient craft, capable of ind ...
s, land-based vehicles (small robots with wheels, cars, or trucks), aerial vehicles, and unmanned aerial vehicles ( UAV). The level of autonomy ranges from fully autonomous (unmanned) vehicles to vehicles where computer-vision-based systems support a driver or a pilot in various situations. Fully autonomous vehicles typically use computer vision for navigation, e.g., for knowing where they are or mapping their environment ( SLAM), for detecting obstacles and/or automatically ensuring navigational safety. It can also be used for detecting certain task-specific events, ''e.g.'', a UAV looking for forest fires. Examples of supporting systems are obstacle warning systems in cars and systems for autonomous landing of aircraft. Several car manufacturers have demonstrated systems for autonomous driving of cars, but this technology has still not reached a level where it can be put on the market. There are ample examples of military autonomous vehicles ranging from advanced missiles to UAVs for recon missions or missile guidance. Space exploration is already being made with autonomous vehicles using computer vision, ''e.g.'',
NASA The National Aeronautics and Space Administration (NASA ) is an independent agencies of the United States government, independent agency of the US federal government responsible for the civil List of government space agencies, space program ...
's ''
Curiosity Curiosity (from Latin '' cūriōsitās'', from ''cūriōsus'' "careful, diligent, curious", akin to ''cura'' "care") is a quality related to inquisitive thinking In their most common sense, the terms thought and thinking refer to consciousn ...
'' and
CNSA China National Space Administration (CNSA; ) is the government agency of the People's Republic of China that is responsible for civil space administration and international space cooperation, including organizing or leading foreign exchanges ...
's ''
Yutu-2 ''Yutu-2'' is the robotic lunar rover component of China National Space Administration, CNSA's Chang'e 4 mission to the Moon, launched on 7 December 2018 18:23 UTC, it entered lunar orbit on 12 December 2018 before making the first soft landing ...
'' rover.


Tactile feedback

Materials such as rubber and silicon are being used to create sensors that allow for applications such as detecting micro undulations and calibrating robotic hands. Rubber can be used in order to create a mold that can be placed over a finger, inside of this mold would be multiple strain gauges. The finger mold and sensors could then be placed on top of a small sheet of rubber containing an array of rubber pins. A user can then wear the finger mold and trace a surface. A computer can then read the data from the strain gauges and measure if one or more of the pins is being pushed upward. If a pin is being pushed upward then the computer can recognize this as an imperfection in the surface. This sort of technology is useful in order to receive accurate data on imperfections on a very large surface. Another variation of this finger mold sensor are sensors that contain a camera suspended in silicon. The silicon forms a dome around the outside of the camera and embedded in the silicon are point markers that are equally spaced. These cameras can then be placed on devices such as robotic hands in order to allow the computer to receive highly accurate tactile data. Other application areas include: * Support of
visual effects Visual effects (sometimes abbreviated VFX) is the process by which imagery is created or manipulated outside the context of a live-action shot in filmmaking and video production. The integration of live-action footage and other live-action foota ...
creation for cinema and broadcast, ''e.g.'', camera tracking (match moving). *
Surveillance Surveillance is the monitoring of behavior, many activities, or information for the purpose of information gathering, influencing, managing or directing. This can include observation from a distance by means of electronic equipment, such as c ...
. * Driver drowsiness detection * Tracking and counting organisms in the biological sciences


Typical tasks

Each of the application areas described above employ a range of computer vision tasks; more or less well-defined measurement problems or processing problems, which can be solved using a variety of methods. Some examples of typical computer vision tasks are presented below. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, ''e.g.'', in the forms of decisions. Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that can interface with other thought processes and elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory.


Recognition

The classical problem in computer vision, image processing, and
machine vision Machine vision (MV) is the technology and methods used to provide image, imaging-based automation, automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine ...
is that of determining whether or not the image data contains some specific object, feature, or activity. Different varieties of recognition problem are described in the literature. *
Object recognition Object recognition – technology in the field of computer vision Computer vision is an Interdisciplinarity, interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. ...
(also called object classification)one or several pre-specified or learned objects or object classes can be recognized, usually together with their 2D positions in the image or 3D poses in the scene. Blippar, Google Goggles, and LikeThat provide stand-alone programs that illustrate this functionality. * Identificationan individual instance of an object is recognized. Examples include identification of a specific person's face or fingerprint, identification of handwritten digits, or identification of a specific vehicle. *
Detection {{Unreferenced, date=March 2018 In general, detection is the action of accessing information without specific cooperation from with the sender. In the history of radio communications, the term "detector (radio), detector" was first used for a devi ...
the image data are scanned for a specific condition. Examples include the detection of possible abnormal cells or tissues in medical images or the detection of a vehicle in an automatic road toll system. Detection based on relatively simple and fast computations is sometimes used for finding smaller regions of interesting image data which can be further analyzed by more computationally demanding techniques to produce a correct interpretation. Currently, the best algorithms for such tasks are based on
convolutional neural network In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of artificial neural network (ANN), most commonly applied to analyze visual imagery. CNNs are also known as Shift Invariant or Space Invariant Artificial Neural Networ ...
s. An illustration of their capabilities is given by the ImageNet Large Scale Visual Recognition Challenge; this is a benchmark in object classification and detection, with millions of images and 1000 object classes used in the competition. Performance of convolutional neural networks on the ImageNet tests is now close to that of humans. The best algorithms still struggle with objects that are small or thin, such as a small ant on a stem of a flower or a person holding a quill in their hand. They also have trouble with images that have been distorted with filters (an increasingly common phenomenon with modern digital cameras). By contrast, those kinds of images rarely trouble humans. Humans, however, tend to have trouble with other issues. For example, they are not good at classifying objects into fine-grained classes, such as the particular breed of dog or species of bird, whereas convolutional neural networks handle this with ease. Several specialized tasks based on recognition exist, such as: *
Content-based image retrieval Content-based image retrieval, also known as query by image content ( QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision Computer vision is an Interdisciplinarity, interdisciplinary scientific fie ...
finding all images in a larger set of images which have a specific content. The content can be specified in different ways, for example in terms of similarity relative to a target image (give me all images similar to image X) by utilizing reverse image search techniques, or in terms of high-level search criteria given as text input (give me all images which contain many houses, are taken during winter and have no cars in them). *
Pose estimation 3D pose estimation is a process of predicting the transformation of an object from a user-defined reference pose, given an image or a 3D scan. It arises in computer vision Computer vision is an Interdisciplinarity, interdisciplinary scientifi ...
estimating the position or orientation of a specific object relative to the camera. An example application for this technique would be assisting a robot arm in retrieving objects from a conveyor belt in an
assembly line An assembly line is a manufacturing process (often called a ''progressive assembly'') in which parts (usually interchangeable parts) are added as the semi-finished assembly moves from workstation to workstation where the parts are added in sequ ...
situation or picking parts from a bin. *
Optical character recognition Optical character recognition or optical character reader (OCR) is the electronics, electronic or machine, mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo ...
(OCR)identifying characters in images of printed or handwritten text, usually with a view to encoding the text in a format more amenable to editing or indexing (''e.g.''
ASCII ASCII ( ), abbreviated from American Standard Code for Information Interchange, is a character encoding standard for electronic communication. ASCII codes represent text in computers, telecommunications equipment, and other devices. Because of ...
). * 2D code readingreading of 2D codes such as
data matrix A Data Matrix is a two-dimensional code consisting of black and white "cells" or dots arranged in either a square (geometry), square or rectangle, rectangular pattern, also known as a matrix (mathematics), matrix. The information to be encoded ...
and QR codes. * Facial recognition a technology that enables the matching of faces in digital images or video frames to a face database, which is now widely used for mobile phone facelock, smart door locking, etc. * Shape Recognition Technology (SRT) in
people counter A people counter is an electronic device that is used to measure the number of people traversing a certain passage or entrance. Examples include simple manual clickers, smart-flooring technologies, infrared beams, thermal imaging systems, WiFi track ...
systems differentiating human beings (head and shoulder patterns) from objects


Motion analysis

Several tasks relate to motion estimation where an image sequence is processed to produce an estimate of the velocity either at each points in the image or in the 3D scene or even of the camera that produces the images. Examples of such tasks are: * Egomotiondetermining the 3D rigid motion (rotation and translation) of the camera from an image sequence produced by the camera. *
Tracking Tracking may refer to: Science and technology Computing * Tracking, in computer graphics, in match moving (insertion of graphics into footage) * Tracking, composing music with music tracker software * Eye tracking, measuring the position of t ...
following the movements of a (usually) smaller set of interest points or objects (''e.g.'', vehicles, objects, humans or other organisms) in the image sequence. This has vast industry applications as most of high-running machinery can be monitored in this way. *
Optical flow Optical flow or optic flow is the pattern of apparent motion (physics), motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer and a scene. Optical flow can also be defined as the distribution o ...
to determine, for each point in the image, how that point is moving relative to the image plane, ''i.e.'', its apparent motion. This motion is a result both of how the corresponding 3D point is moving in the scene and how the camera is moving relative to the scene.


Scene reconstruction

Given one or (typically) more images of a scene, or a video, scene reconstruction aims at computing a 3D model of the scene. In the simplest case, the model can be a set of 3D points. More sophisticated methods produce a complete 3D surface model. The advent of 3D imaging not requiring motion or scanning, and related processing algorithms is enabling rapid advances in this field. Grid-based 3D sensing can be used to acquire 3D images from multiple angles. Algorithms are now available to stitch multiple 3D images together into point clouds and 3D models.


Image restoration

The aim of image restoration is the removal of noise (sensor noise, motion blur, etc.) from images. The simplest possible approach for noise removal is various types of filters such as low-pass filters or median filters. More sophisticated methods assume a model of how the local image structures look, to distinguish them from noise. By first analyzing the image data in terms of the local image structures, such as lines or edges, and then controlling the filtering based on local information from the analysis step, a better level of noise removal is usually obtained compared to the simpler approaches. An example in this field is inpainting.


System methods

The organization of a computer vision system is highly application-dependent. Some systems are stand-alone applications that solve a specific measurement or detection problem, while others constitute a sub-system of a larger design which, for example, also contains sub-systems for control of mechanical actuators, planning, information databases, man-machine interfaces, etc. The specific implementation of a computer vision system also depends on whether its functionality is pre-specified or if some part of it can be learned or modified during operation. Many functions are unique to the application. There are, however, typical functions that are found in many computer vision systems. * Image acquisition – A digital image is produced by one or several
image sensor An image sensor or imager is a sensor that detects and conveys information used to make an image An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual s ...
s, which, besides various types of light-sensitive cameras, include range sensors, tomography devices, radar, ultra-sonic cameras, etc. Depending on the type of sensor, the resulting image data is an ordinary 2D image, a 3D volume, or an image sequence. The pixel values typically correspond to light intensity in one or several spectral bands (gray images or colour images), but can also be related to various physical measures, such as depth, absorption or reflectance of sonic or electromagnetic waves, or
nuclear magnetic resonance Nuclear magnetic resonance (NMR) is a physical phenomenon in which atomic nucleus, nuclei in a strong constant magnetic field are perturbed by a weak oscillating magnetic field (in the near and far field, near field) and respond by producing ...
. * Pre-processing – Before a computer vision method can be applied to image data in order to extract some specific piece of information, it is usually necessary to process the data in order to assure that it satisfies certain assumptions implied by the method. Examples are: ** Re-sampling to assure that the image coordinate system is correct. ** Noise reduction to assure that sensor noise does not introduce false information. ** Contrast enhancement to assure that relevant information can be detected. **
Scale space Scale-space theory is a framework for Multiscale mathematics, multi-scale Signal (information theory), signal Knowledge representation, representation developed by the computer vision, image processing and signal processing communities with compl ...
representation to enhance image structures at locally appropriate scales. *
Feature extraction In machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial in ...
– Image features at various levels of complexity are extracted from the image data. Typical examples of such features are: ** Lines, edges and
ridges A ridge or a mountain ridge is a geographical feature consisting of a chain of mountains or hills that form a continuous elevated crest for an extended distance. The sides of the ridge slope away from the narrow top on either side. The line ...
. ** Localized interest points such as corners, blobs or points. :More complex features may be related to texture, shape or motion. *
Detection {{Unreferenced, date=March 2018 In general, detection is the action of accessing information without specific cooperation from with the sender. In the history of radio communications, the term "detector (radio), detector" was first used for a devi ...
/ segmentation – At some point in the processing a decision is made about which image points or regions of the image are relevant for further processing. Examples are: ** Selection of a specific set of interest points. ** Segmentation of one or multiple image regions that contain a specific object of interest. ** Segmentation of image into nested scene architecture comprising foreground, object groups, single objects or salient object parts (also referred to as spatial-taxon scene hierarchy), while the visual salience is often implemented as spatial and temporal attention. ** Segmentation or co-segmentation of one or multiple videos into a series of per-frame foreground masks, while maintaining its temporal semantic continuity. * High-level processing – At this step the input is typically a small set of data, for example a set of points or an image region which is assumed to contain a specific object. The remaining processing deals with, for example: ** Verification that the data satisfy model-based and application-specific assumptions. ** Estimation of application-specific parameters, such as object pose or object size. **
Image recognition Computer vision is an interdisciplinary scientific field that deals with how computer A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations (computation) automatically. Modern digital ...
– classifying a detected object into different categories. **
Image registration Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, data from different sensors, times, depths, or viewpoints. It is used in computer vision, medical imaging, milit ...
– comparing and combining two different views of the same object. * Decision making Making the final decision required for the application, for example: ** Pass/fail on automatic inspection applications. ** Match/no-match in recognition applications. ** Flag for further human review in medical, military, security and recognition applications.


Image-understanding systems

Image-understanding systems (IUS) include three levels of abstraction as follows: low level includes image primitives such as edges, texture elements, or regions; intermediate level includes boundaries, surfaces and volumes; and high level includes objects, scenes, or events. Many of these requirements are entirely topics for further research. The representational requirements in the designing of IUS for these levels are: representation of prototypical concepts, concept organization, spatial knowledge, temporal knowledge, scaling, and description by comparison and differentiation. While inference refers to the process of deriving new, not explicitly represented facts from currently known facts, control refers to the process that selects which of the many inference, search, and matching techniques should be applied at a particular stage of processing. Inference and control requirements for IUS are: search and hypothesis activation, matching and hypothesis testing, generation and use of expectations, change and focus of attention, certainty and strength of belief, inference and goal satisfaction.


Hardware

There are many kinds of computer vision systems; however, all of them contain these basic elements: a power source, at least one image acquisition device (camera, ccd, etc.), a processor, and control and communication cables or some kind of wireless interconnection mechanism. In addition, a practical vision system contains software, as well as a display in order to monitor the system. Vision systems for inner spaces, as most industrial ones, contain an illumination system and may be placed in a controlled environment. Furthermore, a completed system includes many accessories such as camera supports, cables and connectors. Most computer vision systems use visible-light cameras passively viewing a scene at frame rates of at most 60 frames per second (usually far slower). A few computer vision systems use image-acquisition hardware with active illumination or something other than visible light or both, such as
structured-light 3D scanner A structured-light 3D scanner is a 3D scanning device for measuring the three-dimensional shape of an object using projected light patterns and a camera A camera is an optical instrument that can capture an image. Most cameras can capture ...
s,
thermographic camera Infrared thermography (IRT), thermal video and/or thermal imaging, is a process where a Thermographic camera, thermal camera captures and creates an image of an object by using infrared radiation emitted from the object in a process, which are ...
s, hyperspectral imagers,
radar imaging Imaging radar is an application of radar which is used to create two-dimensional images, typically of landscapes. Imaging radar provides its light to illuminate an area on the ground and take a picture at radio wavelengths. It uses an antenna and ...
,
lidar Lidar (, also LIDAR, or LiDAR; sometimes LADAR) is a method for determining ranging, ranges (variable distance) by targeting an object or a surface with a laser and measuring the time for the reflected light to return to the receiver. It can ...
scanners, magnetic resonance images,
side-scan sonar Side-scan sonar (also sometimes called side scan sonar, sidescan sonar, side imaging sonar, side-imaging sonar and bottom classification sonar) is a category of sonar system that is used to efficiently Seafloor mapping, create an image of large ...
, synthetic aperture sonar, etc. Such hardware captures "images" that are then processed often using the same computer vision algorithms used to process visible-light images. While traditional broadcast and consumer video systems operate at a rate of 30 frames per second, advances in
digital signal processing Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The digital signals processed in this manner are a ...
and consumer graphics hardware has made high-speed image acquisition, processing, and display possible for real-time systems on the order of hundreds to thousands of frames per second. For applications in robotics, fast, real-time video systems are critically important and often can simplify the processing needed for certain algorithms. When combined with a high-speed projector, fast image acquisition allows 3D measurement and feature tracking to be realized. Egocentric vision systems are composed of a wearable camera that automatically take pictures from a first-person perspective. As of 2016,
vision processing unit A vision processing unit (VPU) is (as of 2018) an emerging class of microprocessor; it is a specific type of AI accelerator, designed to hardware acceleration, accelerate machine vision tasks. Overview Vision processing units are distinct from ...
s are emerging as a new class of processor, to complement CPUs and graphics processing units (GPUs) in this role.


See also

* Computational imaging * Computational photography * Computer audition * Egocentric vision * Machine vision glossary *
Space mapping The space mapping methodology for modeling and design optimization of engineering systems was first discovered by John Bandler in 1993. It uses relevant existing knowledge to speed up model generation and design optimization Mathematica ...
*
Teknomo–Fernandez algorithm The Teknomo–Fernandez algorithm (TF algorithm), is an efficient algorithm for generating the background image of a given video sequence. By assuming that the background image is shown in the majority of the video, the algorithm is able to gener ...
*
Vision science Vision science is the scientific study of visual perception. Researchers in vision science can be called vision scientists, especially if their research spans some of the science's many disciplines. Vision science encompasses all studies of visio ...
*
Visual agnosia Visual agnosia is an impairment in recognition of visually presented objects. It is not due to a deficit in vision (acuity, visual field, and scanning), language, memory, or intellect. While cortical blindness results from lesions to primary visual ...
*
Visual perception Visual perception is the ability to interpret the surrounding Biophysical environment, environment through photopic vision (daytime vision), color vision, scotopic vision (night vision), and mesopic vision (twilight vision), using light in the ...
*
Visual system The visual system comprises the sensory organ (the eye) and parts of the central nervous system (the retina containing photoreceptor cells, the optic nerve, the optic tract and the visual cortex) which gives organisms the sense of sight (the a ...


Lists

* Outline of computer vision *
List of emerging technologies This is a list of emerging technologies Emerging technologies are technologies whose development, practical applications, or both are still largely unrealized. These technologies are generally new but also include older technologies fi ...
* Outline of artificial intelligence


References


Further reading

* * * * * * * * * * * * * * * * * * * * * *


External links


USC Iris computer vision conference list


A complete list of papers of the most relevant computer vision conferences.
Computer Vision Online
News, source code, datasets and job offers related to computer vision.
CVonline
Bob Fisher's Compendium of Computer Vision.
British Machine Vision Association
Supporting computer vision research within the UK via the BMVC and MIUA conferences, ''Annals of the BMVA'' (open-source journal), BMVA Summer School and one-day meetings
Computer Vision Container, Joe Hoeller GitHub:
Widely adopted open-source container for GPU accelerated computer vision applications. Used by researchers, universities, private companies as well as the U.S. Gov't. {{Authority control Image processing Packaging machinery Articles containing video clips