{"title":"Reliable multi-object tracking dealing with occlusions for a smart camera","authors":"Aziz Dziri, M. Duranton, R. Chapuis","doi":"10.1145/2789116.2789119","DOIUrl":null,"url":null,"abstract":"In this paper, a multi-object tracking system designed for a low cost embedded smart camera is proposed. Objects tracking constitutes a main step in video-surveillance applications. Because of the number of cameras used to cover a large area, surveillance applications are constrained by the cost of each node, the power efficiency of the system, the robustness of the tracking algorithm and the real-time processing. They require a reliable multi-object tracking algorithm that can run in a real-time on light computing architectures. In this paper, we propose a tracking pipeline designed for a fixed smart camera that can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on the RaspberryPi board equipped with the RaspiCam camera. The tracking quality of the proposed pipeline is evaluated on publicly available datatsets: PETS2009 and CAVIAR.","PeriodicalId":113163,"journal":{"name":"Proceedings of the 9th International Conference on Distributed Smart Cameras","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 9th International Conference on Distributed Smart Cameras","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2789116.2789119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, a multi-object tracking system designed for a low cost embedded smart camera is proposed. Objects tracking constitutes a main step in video-surveillance applications. Because of the number of cameras used to cover a large area, surveillance applications are constrained by the cost of each node, the power efficiency of the system, the robustness of the tracking algorithm and the real-time processing. They require a reliable multi-object tracking algorithm that can run in a real-time on light computing architectures. In this paper, we propose a tracking pipeline designed for a fixed smart camera that can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on the RaspberryPi board equipped with the RaspiCam camera. The tracking quality of the proposed pipeline is evaluated on publicly available datatsets: PETS2009 and CAVIAR.