Extrinsic Parameters
Camera resectioning is the process of estimating the parameters of a pinhole camera model approximating the camera that produced a given photograph or video; it determines which incoming light ray is associated with each pixel on the resulting image. Basically, the process determines the pose of the pinhole camera. Usually, the camera parameters are represented in a 3 × 4 projection matrix called the ''camera matrix''. The extrinsic parameters define the camera ''pose'' (position and orientation) while the intrinsic parameters specify the camera image format (focal length, pixel size, and image origin). This process is often called geometric camera calibration or simply camera calibration, although that term may also refer to photometric camera calibration or be restricted for the estimation of the intrinsic parameters only. Exterior orientation and interior orientation refer to the determination of only the extrinsic and intrinsic parameters, respectively. The cla ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Pinhole Camera Model
The pinhole camera model describes the mathematical relationship between the coordinates of a point in three-dimensional space and its projection onto the image plane of an ''ideal'' pinhole camera, where the camera aperture is described as a point and no lenses are used to focus light. The model does not include, for example, geometric distortions or blurring of unfocused objects caused by lenses and finite sized apertures. It also does not take into account that most practical cameras have only discrete image coordinates. This means that the pinhole camera model can only be used as a first order approximation of the mapping from a 3D scene to a 2D image. Its validity depends on the quality of the camera and, in general, decreases from the center of the image to the edges as lens distortion effects increase. Some of the effects that the pinhole camera model does not take into account can be compensated, for example by applying suitable coordinate transformations on the ima ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Bundle Adjustment
In photogrammetry and computer stereo vision, bundle adjustment is simultaneous refining of the 3D coordinates describing the scene geometry, the parameters of the relative motion, and the optical characteristics of the camera(s) employed to acquire the images, given a set of images depicting a number of 3D points from different viewpoints. Its name refers to the '' geometrical bundles'' of light rays originating from each 3D feature and converging on each camera's optical center, which are adjusted optimally according to an optimality criterion involving the corresponding image projections of all points. Uses Bundle adjustment is almost always used as the last step of every feature-based 3D reconstruction algorithm. It amounts to an optimization problem on the 3D structure and viewing parameters (i.e., camera pose and possibly intrinsic calibration and radial distortion), to obtain a reconstruction which is optimal under certain assumptions regarding the noise pertaining t ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Pinhole Camera Model
The pinhole camera model describes the mathematical relationship between the coordinates of a point in three-dimensional space and its projection onto the image plane of an ''ideal'' pinhole camera, where the camera aperture is described as a point and no lenses are used to focus light. The model does not include, for example, geometric distortions or blurring of unfocused objects caused by lenses and finite sized apertures. It also does not take into account that most practical cameras have only discrete image coordinates. This means that the pinhole camera model can only be used as a first order approximation of the mapping from a 3D scene to a 2D image. Its validity depends on the quality of the camera and, in general, decreases from the center of the image to the edges as lens distortion effects increase. Some of the effects that the pinhole camera model does not take into account can be compensated, for example by applying suitable coordinate transformations on the ima ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Mixed Reality
Mixed reality (MR) is a term used to describe the merging of a real-world environment and a computer-generated one. Physical and virtual objects may co-exist in mixed reality environments and interact in real time. Mixed reality is largely synonymous with augmented reality. Mixed reality that incorporates haptics has sometimes been referred to as Visuo-haptic mixed reality. In a physics context, the term "interreality system" refers to a virtual reality system coupled with its real-world counterpart. A 2007 paper describes an interreality system comprising a real physical pendulum coupled to a pendulum that only exists in virtual reality. This system has two stable states of motion: a "Dual Reality" state in which the motion of the two pendula are uncorrelated, and a "Mixed Reality" state in which the pendula exhibit stable phase-locked motion, which is highly correlated. The use of the terms "mixed reality" and "interreality" is clearly defined in the context of physics and may ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Eight-point Algorithm
The eight-point algorithm is an algorithm used in computer vision to estimate the essential matrix or the fundamental matrix related to a stereo camera pair from a set of corresponding image points. It was introduced by Christopher Longuet-Higgins in 1981 for the case of the essential matrix. In theory, this algorithm can be used also for the fundamental matrix, but in practice the normalized eight-point algorithm, described by Richard Hartley in 1997, is better suited for this case. The algorithm's name derives from the fact that it estimates the essential matrix or the fundamental matrix from a set of eight (or more) corresponding image points. However, variations of the algorithm can be used for fewer than eight points. Coplanarity constraint One may express the epipolar geometry of two cameras and a point in space with an algebraic equation. Observe that, no matter where the point P is in space, the vectors \overline, \overline and \overline belong to the same plane ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Augmented Virtuality
Mixed reality (MR) is a term used to describe the merging of a real-world environment and a computer-generated one. Physical and virtual objects may co-exist in mixed reality environments and interact in real time. Mixed reality is largely synonymous with augmented reality. Mixed reality that incorporates haptics has sometimes been referred to as Visuo-haptic mixed reality. In a physics context, the term "interreality system" refers to a virtual reality system coupled with its real-world counterpart. A 2007 paper describes an interreality system comprising a real physical pendulum coupled to a pendulum that only exists in virtual reality. This system has two stable states of motion: a "Dual Reality" state in which the motion of the two pendula are uncorrelated, and a "Mixed Reality" state in which the pendula exhibit stable phase-locked motion, which is highly correlated. The use of the terms "mixed reality" and "interreality" is clearly defined in the context of physics and may ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Augmented Reality
Augmented reality (AR) is an interactive experience that combines the real world and computer-generated content. The content can span multiple sensory modalities, including visual, auditory, haptic, somatosensory and olfactory. AR can be defined as a system that incorporates three basic features: a combination of real and virtual worlds, real-time interaction, and accurate 3D registration of virtual and real objects. The overlaid sensory information can be constructive (i.e. additive to the natural environment), or destructive (i.e. masking of the natural environment). This experience is seamlessly interwoven with the physical world such that it is perceived as an immersive aspect of the real environment. In this way, augmented reality alters one's ongoing perception of a real-world environment, whereas virtual reality completely replaces the user's real-world environment with a simulated one. Augmented reality is largely synonymous with mixed reality. There is also overlap ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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3D 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 or robotics where the pose or transformation of an object can be used for alignment of a computer-aided design models, identification, grasping, or manipulation of the object. The image data from which the pose of an object is determined can be either a single image, a stereo image pair, or an image sequence where, typically, the camera is moving with a known velocity. The objects which are considered can be rather general, including a living being or body parts, e.g., a head or hands. The methods which are used for determining the pose of an object, however, are usually specific for a class of objects and cannot generally be expected to work well for other types of objects. From an uncalibrated 2D camera It is possible to estimate the 3D rotation and translation of a 3D object from a single 2D photo, if an ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Homography (computer Vision)
In the field of computer vision, any two images of the same planar surface in space are related by a homography (assuming a pinhole camera model). This has many practical applications, such as image rectification, image registration, or camera motion—rotation and translation—between two images. Once camera resectioning has been done from an estimated homography matrix, this information may be used for navigation, or to insert models of 3D objects into an image or video, so that they are rendered with the correct perspective and appear to have been part of the original scene (see Augmented reality). 3D plane to plane equation We have two cameras ''a'' and ''b'', looking at points P_i in a plane. Passing from the projection ^bp_i=\left(^bu_i;^bv_i;1\right) of P_i in ''b'' to the projection ^ap_i=\left(^au_i;^av_i;1\right) of P_i in ''a'': : ^ap_i = \fracK_a \cdot H_ \cdot K_b^ \cdot ^bp_i where ^az_i and ^bz_i are the z coordinates of P in each camera frame and where the ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Direct Linear Transformation
Direct linear transformation (DLT) is an algorithm which solves a set of variables from a set of similarity relations: : \mathbf_ \propto \mathbf \, \mathbf_ for \, k = 1, \ldots, N where \mathbf_ and \mathbf_ are known vectors, \, \propto denotes equality up to an unknown scalar multiplication, and \mathbf is a matrix (or linear transformation) which contains the unknowns to be solved. This type of relation appears frequently in projective geometry. Practical examples include the relation between 3D points in a scene and their projection onto the image plane of a pinhole camera, and homographies. Introduction An ordinary system of linear equations : \mathbf_ = \mathbf \, \mathbf_ for \, k = 1, \ldots, N can be solved, for example, by rewriting it as a matrix equation \mathbf = \mathbf \, \mathbf where matrices \mathbf and \mathbf contain the vectors \mathbf_ and \mathbf_ in their respective columns. Given that there exists a unique ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Direct Linear Transformation
Direct linear transformation (DLT) is an algorithm which solves a set of variables from a set of similarity relations: : \mathbf_ \propto \mathbf \, \mathbf_ for \, k = 1, \ldots, N where \mathbf_ and \mathbf_ are known vectors, \, \propto denotes equality up to an unknown scalar multiplication, and \mathbf is a matrix (or linear transformation) which contains the unknowns to be solved. This type of relation appears frequently in projective geometry. Practical examples include the relation between 3D points in a scene and their projection onto the image plane of a pinhole camera, and homographies. Introduction An ordinary system of linear equations : \mathbf_ = \mathbf \, \mathbf_ for \, k = 1, \ldots, N can be solved, for example, by rewriting it as a matrix equation \mathbf = \mathbf \, \mathbf where matrices \mathbf and \mathbf contain the vectors \mathbf_ and \mathbf_ in their respective columns. Given that there exists a unique ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |
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Pixel
In digital imaging, a pixel (abbreviated px), pel, or picture element is the smallest addressable element in a raster image, or the smallest point in an all points addressable display device. In most digital display devices, pixels are the smallest element that can be manipulated through software. Each pixel is a sample of an original image; more samples typically provide more accurate representations of the original. The intensity of each pixel is variable. In color imaging systems, a color is typically represented by three or four component intensities such as red, green, and blue, or cyan, magenta, yellow, and black. In some contexts (such as descriptions of camera sensors), ''pixel'' refers to a single scalar element of a multi-component representation (called a ''photosite'' in the camera sensor context, although ''sensel'' is sometimes used), while in yet other contexts (like MRI) it may refer to a set of component intensities for a spatial position. Etymology The w ... [...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]   |