Sources:IEEE Transactions on Pattern Analysis and Machine Intelligence 31(6):974-988,2009
Authors: Zhang Guofeng; Jia Jiaya; Wong Tien-Tsin; Bao Hujun
We propose a novel method for recovering high-quality depth maps from a video sequence. We introduce a bundle optimization framework which models the matching ambiguities with multiple frames in a statistical way. This framework effectively addresses the major difficulties in stereo reconstruction, such as image noise, occlusions and outliers, and can produce sharp and temporal consistent object boundaries among different frames. The recovered high-quality dense depth maps can facilitate many related applications, and lay a solid foundation for complex video editing and processing.