Daniela Hall, J. Nascimento, P. Ribeiro, E. Andrade, Plinio Moreno, S. Pesnel, T. List, R. Emonet, R. Fisher, J. S. Victor, J. Crowley
{"title":"基于自适应背景模型的目标检测算法比较","authors":"Daniela Hall, J. Nascimento, P. Ribeiro, E. Andrade, Plinio Moreno, S. Pesnel, T. List, R. Emonet, R. Fisher, J. S. Victor, J. Crowley","doi":"10.1109/VSPETS.2005.1570905","DOIUrl":null,"url":null,"abstract":"This article compares the performance of target detectors based on adaptive background differencing on public benchmark data. Five state of the art methods are described. The performance is evaluated using state of the art measures with respect to ground truth. The original points are the comparison to hand labelled ground truth and the evaluation on a large database. The simpler methods LOTS and SGM are more appropriate to the particular task as MGM using a more complex background model.","PeriodicalId":435841,"journal":{"name":"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"124","resultStr":"{\"title\":\"Comparison of target detection algorithms using adaptive background models\",\"authors\":\"Daniela Hall, J. Nascimento, P. Ribeiro, E. Andrade, Plinio Moreno, S. Pesnel, T. List, R. Emonet, R. Fisher, J. S. Victor, J. Crowley\",\"doi\":\"10.1109/VSPETS.2005.1570905\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article compares the performance of target detectors based on adaptive background differencing on public benchmark data. Five state of the art methods are described. The performance is evaluated using state of the art measures with respect to ground truth. The original points are the comparison to hand labelled ground truth and the evaluation on a large database. The simpler methods LOTS and SGM are more appropriate to the particular task as MGM using a more complex background model.\",\"PeriodicalId\":435841,\"journal\":{\"name\":\"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"124\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VSPETS.2005.1570905\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VSPETS.2005.1570905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of target detection algorithms using adaptive background models
This article compares the performance of target detectors based on adaptive background differencing on public benchmark data. Five state of the art methods are described. The performance is evaluated using state of the art measures with respect to ground truth. The original points are the comparison to hand labelled ground truth and the evaluation on a large database. The simpler methods LOTS and SGM are more appropriate to the particular task as MGM using a more complex background model.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
