{"title":"Video Stereo Matching with Temporally Consistent Belief Propagation","authors":"Hsin-Yu Hou, Sih-Sian Wu, Da-Fang Chang, Liang-Gee Chen","doi":"10.1109/ICME.2018.8486493","DOIUrl":null,"url":null,"abstract":"The belief propagation (BP) technique is successful in image stereo matching problem. However, when we consider stereo matching for videos, directly applying the BP algorithm frame by frame results in unsatisfactory temporally inconsistent disparity maps. In this paper, we present the temporally consistent belief propagation for video stereo matching. We introduce a temporal term in traditional BP objective function and propose an adaptive weighting scheme to account for this temporal term. We show that the proposed algorithm performs favorably against previous methods in the stereo video datasets. Furthermore, the proposed method can solve problems induced by previous methods like error propagation from previously occluded regions.","PeriodicalId":426613,"journal":{"name":"2018 IEEE International Conference on Multimedia and Expo (ICME)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Multimedia and Expo (ICME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2018.8486493","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The belief propagation (BP) technique is successful in image stereo matching problem. However, when we consider stereo matching for videos, directly applying the BP algorithm frame by frame results in unsatisfactory temporally inconsistent disparity maps. In this paper, we present the temporally consistent belief propagation for video stereo matching. We introduce a temporal term in traditional BP objective function and propose an adaptive weighting scheme to account for this temporal term. We show that the proposed algorithm performs favorably against previous methods in the stereo video datasets. Furthermore, the proposed method can solve problems induced by previous methods like error propagation from previously occluded regions.