{"title":"A framework for modeling appearance change in image sequences","authors":"Michael J. Black, David J. Fleet, Y. Yacoob","doi":"10.1109/ICCV.1998.710788","DOIUrl":null,"url":null,"abstract":"Image \"appearance\" may change over time due to a variety of causes such as: 1) object or camera motion; 2) generic photometric events including variations in illumination (e.g. shadows) and specular reflections; and 3) \"iconic changes\" which are specific to the objects being viewed and include complex occlusion events and changes in the material properties of the objects. We propose a general framework for representing and recovering these \"appearance changes\" in an image sequence as a \"mixture\" of different causes. The approach generalizes previous work on optical flow to provide a richer description of image events and more reliable estimates of image motion.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"77","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.1998.710788","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 77
Abstract
Image "appearance" may change over time due to a variety of causes such as: 1) object or camera motion; 2) generic photometric events including variations in illumination (e.g. shadows) and specular reflections; and 3) "iconic changes" which are specific to the objects being viewed and include complex occlusion events and changes in the material properties of the objects. We propose a general framework for representing and recovering these "appearance changes" in an image sequence as a "mixture" of different causes. The approach generalizes previous work on optical flow to provide a richer description of image events and more reliable estimates of image motion.
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