{"title":"快速高效的立体深度图计算","authors":"P. Ghosh, K. Venkatesh","doi":"10.1109/3DTV.2013.6676651","DOIUrl":null,"url":null,"abstract":"We present here our approach to the problem of improving the efficiency of stereo depth map computation. The algorithm is applied on rectified images. Graph cut is used for energy minimization. The descriptors used are both SIFT and DAISY. This algorithm produces fast results of approximate disparity maps from two images. The main advantage of our algorithm is its efficiency and reduction of computation time, in spite of an improvement of the error performance. To achieve this, we initially use a sparse global matching technique using SIFT to determine the necessary labels and then find dense correspondence with DAISY.","PeriodicalId":111565,"journal":{"name":"2013 3DTV Vision Beyond Depth (3DTV-CON)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast and efficient computation of stereo depth maps\",\"authors\":\"P. Ghosh, K. Venkatesh\",\"doi\":\"10.1109/3DTV.2013.6676651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present here our approach to the problem of improving the efficiency of stereo depth map computation. The algorithm is applied on rectified images. Graph cut is used for energy minimization. The descriptors used are both SIFT and DAISY. This algorithm produces fast results of approximate disparity maps from two images. The main advantage of our algorithm is its efficiency and reduction of computation time, in spite of an improvement of the error performance. To achieve this, we initially use a sparse global matching technique using SIFT to determine the necessary labels and then find dense correspondence with DAISY.\",\"PeriodicalId\":111565,\"journal\":{\"name\":\"2013 3DTV Vision Beyond Depth (3DTV-CON)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 3DTV Vision Beyond Depth (3DTV-CON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/3DTV.2013.6676651\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 3DTV Vision Beyond Depth (3DTV-CON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3DTV.2013.6676651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast and efficient computation of stereo depth maps
We present here our approach to the problem of improving the efficiency of stereo depth map computation. The algorithm is applied on rectified images. Graph cut is used for energy minimization. The descriptors used are both SIFT and DAISY. This algorithm produces fast results of approximate disparity maps from two images. The main advantage of our algorithm is its efficiency and reduction of computation time, in spite of an improvement of the error performance. To achieve this, we initially use a sparse global matching technique using SIFT to determine the necessary labels and then find dense correspondence with DAISY.