S. Oztürk, Ö. C. Gürol, B. Sankur, B. Acar, Mehmet Güney
{"title":"Vergence region estimation from sparse disparity map","authors":"S. Oztürk, Ö. C. Gürol, B. Sankur, B. Acar, Mehmet Güney","doi":"10.1109/SIU.2012.6204586","DOIUrl":null,"url":null,"abstract":"This paper presents the estimation of the vergence region, which is defined by the set of zero disparity points on the stereo images, in the form of the best border line separating the positive and negative disparities, by using a sparse disparity map. Sparse disparities are summed along radiating directions and the best direction to separate the sparse map is found by means of the metrics defined over the resultant sum function. The resulting border line points correspond to the points which will be perceived on the screen when the scene is displayed in three dimensions. This method requires the use of the stereo images with a certain spatial distribution of disparities, where the positive and negative disparities are grouped together.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 20th Signal Processing and Communications Applications Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2012.6204586","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
This paper presents the estimation of the vergence region, which is defined by the set of zero disparity points on the stereo images, in the form of the best border line separating the positive and negative disparities, by using a sparse disparity map. Sparse disparities are summed along radiating directions and the best direction to separate the sparse map is found by means of the metrics defined over the resultant sum function. The resulting border line points correspond to the points which will be perceived on the screen when the scene is displayed in three dimensions. This method requires the use of the stereo images with a certain spatial distribution of disparities, where the positive and negative disparities are grouped together.