Cooperative Stereo Vision - Robotics Institute Carnegie Mellon University
Cooperative Stereo Vision
Project Head: Takeo Kanade

We are developing a cooperative stereo vision algorithm for obtaining disparity maps and explicitly detecting occlusions. To produce smooth and detailed disparity maps, we utilize two assumptions: uniqueness and continuity. That is, the disparity maps have a unique value per pixel and are continuous almost everywhere.

Our current algorithm has been tested on several benchmark stereo image pairs. Please see our homepage for examples. We are also distributing a sample program to allow others to use our algorithm.

In the future, we hope to develop a more comprehensive package for stereo vision research. This includes creating a program for rectifying stereo image pairs and increasing the usability of our current stereo program.

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