Computer stereo vision

Computer stereo vision is the extraction of 3D information from digital images, such as obtained by a CCD camera. By comparing information about a scene from two vantage points, 3D information can be extracted by examination of the relative positions of objects in the two panels. This is similar to the biological process 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 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.

The conventional structured-light vision (SLV) employs a structured light or laser, and finds projector-camera correspondences.

The conventional active stereo vision (ASV) employs a structured light or laser, however, the stereo matching is performed only for camera-camera correspondences, in the same way as the passive stereo vision.

There is a hybrid technique, which utilizes both camera-camera and projector-camera correspondences.

3D stereo displays finds many applications in entertainment, information transfer and automated systems. Stereo vision is highly important in fields such as robotics, to extract information about the relative position of 3D objects in the vicinity of autonomous systems. Other applications for robotics include object recognition, where depth information allows for the system to separate occluding image components, such as one chair in front of another, which the robot may otherwise not be able to distinguish as a separate object by any other criteria.

Scientific applications for digital stereo vision include the extraction of information from aerial surveys, for calculation of contour maps or even geometry extraction for 3D building mapping, or calculation of 3D heliographical information such as obtained by the NASA STEREO project.

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Wikipedia