Stereo-motion estimation for visual object tracking

Visual object tracking is a problem that has been studied by the computer community for decades. Computational stereo refers to the problem of determining 3-dimensional structure of a scene from two or more images taken from distinct viewpoints. An approach to detect stereo-moving objects with bio-cameras is presented in this thesis. Stereo and motion are detected simultaneously under a modified formulation of energy function. We extend the application from static stereo match and motion mono-camera detection to handle the whole problem together at a time, which results in a reduction of computation time and ability to handle more difficult situation. Experiments on several video-images, that showing convictive object detecting performances demonstrate its strong adaptability to stereo-motion application.