{"title":"Learning crowd behavior for event recognition","authors":"E. Cermeño, Silvana Mallor, Juan Alberto Sigüenza","doi":"10.1109/PETS.2013.6523788","DOIUrl":null,"url":null,"abstract":"This paper presents a new method for event recognition based on machine learning techniques. One machine is trained per kind of event using color, texture and shape features. Testing is performed on the PETS 2009 dataset. We evaluate accuracy of our automatic system with six different kind of events and then compare the results with human classification.","PeriodicalId":385403,"journal":{"name":"2013 IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PETS.2013.6523788","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper presents a new method for event recognition based on machine learning techniques. One machine is trained per kind of event using color, texture and shape features. Testing is performed on the PETS 2009 dataset. We evaluate accuracy of our automatic system with six different kind of events and then compare the results with human classification.
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