{"title":"Constructing Face Image Logs that are Both Complete and Concise","authors":"Adam Fourney, R. Laganière","doi":"10.1109/CRV.2007.20","DOIUrl":null,"url":null,"abstract":"This paper describes a construct that we call a face image log. Face image logs are collections of time stamped images representing faces detected in surveillance videos. The techniques demonstrated in this paper strive to construct face image logs that are complete and concise in the sense that the logs contain only the best images available for each individual observed. We begin by describing how to assess and compare the quality of face images. We then illustrate a robust method for selecting high quality images. This selection process takes into consideration the limitations inherent in existing face detection and person tracking techniques. Experimental results demonstrate that face logs constructed in this manner generally contain fewer than 5% of all detected faces, yet these faces are of high quality, and they represent all individuals detected in the video sequence.","PeriodicalId":304254,"journal":{"name":"Fourth Canadian Conference on Computer and Robot Vision (CRV '07)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth Canadian Conference on Computer and Robot Vision (CRV '07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2007.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31
Abstract
This paper describes a construct that we call a face image log. Face image logs are collections of time stamped images representing faces detected in surveillance videos. The techniques demonstrated in this paper strive to construct face image logs that are complete and concise in the sense that the logs contain only the best images available for each individual observed. We begin by describing how to assess and compare the quality of face images. We then illustrate a robust method for selecting high quality images. This selection process takes into consideration the limitations inherent in existing face detection and person tracking techniques. Experimental results demonstrate that face logs constructed in this manner generally contain fewer than 5% of all detected faces, yet these faces are of high quality, and they represent all individuals detected in the video sequence.