{"title":"Constant Time Stereo Matching","authors":"Myung-Ho Ju, Hang-Bong Kang","doi":"10.1109/IMVIP.2009.10","DOIUrl":null,"url":null,"abstract":"Typically, local methods for stereo matching are fast but have relatively low degree of accuracy while global ones, though costly, achieve a higher degree of accuracy in retrieving disparity information. Recently, however, some local methods such as those based on segmentation or adaptive weights are suggested to possibly achieve more accuracy than global ones in retrieving disparity information. The problem for these newly suggested local methods is that they cannot be easily adopted since they may require more computational costs which increase in proportion to the window size they use. To reduce the computational costs, therefore, we propose in this paper the stereo matching method that use domain weight and range weight similar to those in the bilateral filter. Our proposed method shows constant time O(1) for the stereo matching. Our experiments spend constant time for computation regardless of the window size but our experimental results show that the accuracy of generated depth map is as good as the ones suggested by recent methods.","PeriodicalId":179564,"journal":{"name":"2009 13th International Machine Vision and Image Processing Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 13th International Machine Vision and Image Processing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMVIP.2009.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Typically, local methods for stereo matching are fast but have relatively low degree of accuracy while global ones, though costly, achieve a higher degree of accuracy in retrieving disparity information. Recently, however, some local methods such as those based on segmentation or adaptive weights are suggested to possibly achieve more accuracy than global ones in retrieving disparity information. The problem for these newly suggested local methods is that they cannot be easily adopted since they may require more computational costs which increase in proportion to the window size they use. To reduce the computational costs, therefore, we propose in this paper the stereo matching method that use domain weight and range weight similar to those in the bilateral filter. Our proposed method shows constant time O(1) for the stereo matching. Our experiments spend constant time for computation regardless of the window size but our experimental results show that the accuracy of generated depth map is as good as the ones suggested by recent methods.