High-speed correspondence for object recognition and tracking

Real-time measurement using multi-camera 3D measuring system requires three major components to operate at high speed: image data processing; correspondence; and least squares estimation. This paper is based upon a system developed at City University which uses high speed solutions for the first and last elements, and describes recent work to provide a high speed solution to the correspondence problem. Correspondence has traditionally been solved in photogrammetry by using human stereo fusion of two views of an object providing an immediate solution. Computer vision researchers and photogrammetrists have applied image processing techniques and computers to the same configuration and have developed numerous matching algorithms with considerable success. Where research is still required, and the published work is not so plentiful, is in the area of multi-camera correspondence. The most commonly used methods utilize the epipolar geometry to establish the correspondences. While this method is adequate for some simple situations, extensions to more than just a few cameras are required which are reliable and efficient. In this paper the early stages of research into reliable and efficient multi-camera correspondence method for high speed measurement tasks are reported.