Temporally Consistence Depth Estimation from Stereo Video Sequences

Abstract

In this paper, we propose complexity reduction method in stereo matching. For complexity reduction in video sequences, we start from generating of initial disparity information. Initial disparity information can give a restricted disparity search range when performing the local stereo matching. As an initial disparity information, we use 4 different kinds of input images. The initial disparity information types can divide into two main streams like 'calculated' and 'given' materials. Iterative stereo matching method, motion prediction stereo matching method and global matching result based stereo matching method are used as a 'calculated' initial value. Captured by depth camera image is used as 'given' information. By using those 4 different types of disparity information, we can save the time consuming when performing the local stereo matching with consecutive image sequences. Results of the experiment prove the efficiency of proposed method. By using proposed local stereo matching method, we can finish all procedures within a few seconds and conserve the quality of disparity images.