Stereo vision and 3D reconstruction technologies are increasingly concerned in many fields. Stereo matching algorithm is the core of stereo vision and also a technical difficulty. A novel method based on super pixels is mentioned in this paper to reduce the calculating amount and the time. Stereo images from University of Tsukuba are used to test our method. The proposed method spends only 1% of the time spent by the conventional method. Through a two-step super-pixel matching optimization, it takes 6.72 s to match a picture, which is 12.96% of the pre-optimization.
A trinocular stereo-matching algorithm based on adaptive support-weight and disparity adjustment has been proposed to improve the accuracy of trinocular vision. Adaptive support-weight which is an efficient window selection method in binocular stereo is applied in the trinocular stereo. A robust target image selection method is also proposed for using the information of different target images in trinocular stereo-vision system efficiently. So occlusion can be handled well by this means. The vision system is tested in the project Family Life Support Multi-Robot Systems.
Stereo matching algorithm based on illumination normal similarity and adaptive support weight
