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Object detection is a computer technology related to
It is widely used in
Methods for object detection generally fall into either neural network-based or non-neural approaches. For non-neural approaches, it becomes necessary to first define features using one of the methods below, then using a technique such as
Multiple object class detection
Spatio-temporal action localization
Video object detection and co-segmentation
Object recognition and categorization Surveillance Applications of computer vision Gesture recognition
Object detection is a computer technology related to computer vision
Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the hum ...
and 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 ...
that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. Well-researched domains of object detection include face detection
Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. ...
and pedestrian detection. Object detection has applications in many areas of computer vision, including image retrieval
An image retrieval system is a computer system used for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as caption ...
and video surveillance
Closed-circuit television (CCTV), also known as video surveillance, is the use of video cameras to transmit a signal to a specific place, on a limited set of monitors. It differs from broadcast television in that the signal is not openly tr ...
.
Uses
It is widely used in computer vision
Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the hum ...
tasks such as image annotation, vehicle counting, activity recognition
Activity recognition aims to recognize the actions and goals of one or more agents from a series of observations on the agents' actions and the environmental conditions. Since the 1980s, this research field has captured the attention of several c ...
, face detection
Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. ...
, face recognition
A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and wo ...
, video object co-segmentation. It is also used in tracking objects, for example tracking a ball during a football match, tracking movement of a cricket bat, or tracking a person in a video.
Concept
Every object class has its own specialfeatures
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 ...
that helps in classifying the class – for example all circle
A circle is a shape consisting of all points in a plane that are at a given distance from a given point, the centre. Equivalently, it is the curve traced out by a point that moves in a plane so that its distance from a given point is const ...
s are round.
Object class detection uses these special features. For example, when looking for circles, objects that are at a particular distance from a point (i.e. the center) are sought. Similarly, when looking for squares, objects that are perpendicular
In elementary geometry, two geometric objects are perpendicular if they intersect at a right angle (90 degrees or π/2 radians). The condition of perpendicularity may be represented graphically using the ''perpendicular symbol'', ⟂. It can ...
at corners and have equal side lengths are needed. A similar approach is used for face identification where eyes, nose, and lips can be found and features
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 ...
like skin color and distance between eyes can be found.
Methods
Methods for object detection generally fall into either neural network-based or non-neural approaches. For non-neural approaches, it becomes necessary to first define features using one of the methods below, then using a technique such as support vector machine
In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. Developed at AT&T Bell Laboratorie ...
(SVM) to do the classification. On the other hand, neural techniques are able to do end-to-end object detection without specifically defining features, and are typically 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 Netwo ...
s (CNN).
* Non-neural approaches:
** Viola–Jones object detection framework
The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. It was motivated primarily by the problem of face detection, although it can be adapted to the detecti ...
based on Haar features
** Scale-invariant feature transform (SIFT)
** Histogram of oriented gradients (HOG) features
* Neural network approaches:
** Region Proposals (R-CNN, Fast R-CNN, Faster R-CNN, cascade R-CNN.)
** Single Shot MultiBox Detector (SSD)
** You Only Look Once (YOLO)
** Single-Shot Refinement Neural Network for Object Detection (RefineDet)
** Retina-Net
** Deformable convolutional networks
See also
*Feature detection (computer vision)
In computer vision and image processing, a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as poi ...
* Moving object detection Moving object detection is a technique used in computer vision and image processing. Multiple consecutive frames from a video are compared by various methods to determine if any moving object is detected.
Moving objects detection has been used for ...
* Small object detection
Small object detection is a particular case of object detection where various techniques are employed to detect small objects in digital images and videos. "Small objects" are objects having a small pixel footprint in the input image. In areas suc ...
* Outline of object recognition
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the ...
* 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 ...
References
* * {{cite web , url=http://www.vision.ee.ethz.ch/publications/get_abstract.cgi?procs=560&mode=&lang=en , title=ETHZ – Computer Vision Lab: Publications , publisher=Vision.ee.ethz.ch , access-date=2013-10-09 , archive-url=https://web.archive.org/web/20130603170209/http://www.vision.ee.ethz.ch/publications/get_abstract.cgi?procs=560&mode=&lang=en , archive-date=2013-06-03 , url-status=deadExternal links
Multiple object class detection
Spatio-temporal action localization
Video object detection and co-segmentation
Object recognition and categorization Surveillance Applications of computer vision Gesture recognition