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 positions of objects in the two panels. This is similar to the biological process of stereopsis.
In traditional stereo vision, two cameras, displaced horizontally from one another, are used to obtain two differing views on a scene, in a manner similar to human binocular vision. By comparing these two images, the relative depth information can be obtained in the form of a disparity map, which encodes the difference in horizontal coordinates of corresponding image points. The values in this disparity map are inversely proportional to the scene depth at the corresponding pixel location.
For a human to compare the two images, they must be superimposed in a stereoscopic device, with the image from the right camera being shown to the observer's right eye and from the left one to the left eye.
In a computer vision system, several pre-processing steps are required.
The image must first be undistorted, such that barrel distortion and tangential distortion are removed. This ensures that the observed image matches the projection of an ideal pinhole camera.
The image must be projected back to a common plane to allow comparison of the image pairs, known as .
An information measure which compares the two images is minimized. This gives the best estimate of the position of features in the two images, and creates a disparity map.
Optionally, the received disparity map is projected into a 3d point cloud. By utilising the cameras' projective parameters, the point cloud can be computed such that it provides measurements at a known scale.
The active stereo vision is a form of stereo vision which actively employs a light such as a laser or a structured light to simplify the stereo matching problem. The opposed term is passive stereo vision.
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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.
Stereopsis () is the component of depth perception retrieved through binocular vision. Stereopsis is not the only contributor to depth perception, but it is a major one. Binocular vision happens because each eye receives a different image because they are in slightly different positions on one's head (left and right eyes). These positional differences are referred to as "horizontal disparities" or, more generally, "binocular disparities". Disparities are processed in the visual cortex of the brain to yield depth perception.
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