{"title":"Group detection in still images by F-formation modeling: A comparative study","authors":"F. Setti, H. Hung, M. Cristani","doi":"10.1109/WIAMIS.2013.6616147","DOIUrl":null,"url":null,"abstract":"Automatically detecting groups of conversing people has become a hot challenge, although a formal, widely-accepted definition of them is lacking. This gap can be filled by considering the social psychological notion of an F-formation as a loose geometric arrangement. In the literature, two main approaches followed this line, exploiting Hough voting [1] from one side and Graph Theory [2] on the other. This paper offers a thorough comparison of these two methods, highlighting the strengths and weaknesses of both in different real life scenarios. Our experiments demonstrate a deeper understanding of the problem by identifying the circumstances in which to adopt a particular method. Finally our study outlines what aspects of the problem are important to address for future improvements to this task.","PeriodicalId":408077,"journal":{"name":"2013 14th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 14th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIAMIS.2013.6616147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 37
Abstract
Automatically detecting groups of conversing people has become a hot challenge, although a formal, widely-accepted definition of them is lacking. This gap can be filled by considering the social psychological notion of an F-formation as a loose geometric arrangement. In the literature, two main approaches followed this line, exploiting Hough voting [1] from one side and Graph Theory [2] on the other. This paper offers a thorough comparison of these two methods, highlighting the strengths and weaknesses of both in different real life scenarios. Our experiments demonstrate a deeper understanding of the problem by identifying the circumstances in which to adopt a particular method. Finally our study outlines what aspects of the problem are important to address for future improvements to this task.