{"title":"无线视频传感器网络协同多目标跟踪方法","authors":"Zheng Chu, L. Zhuo, Yingdi Zhao, Xiaoguang Li","doi":"10.1109/MMSP.2011.6093796","DOIUrl":null,"url":null,"abstract":"For the enormous number and the limited energy of network nodes in the wireless video sensor networks (WVSN) environment, to fulfil the complicated tasks, multiple sensor nodes should collaborate with each other. A cooperative multi-object tracking method for Wireless Video Sensor Networks is proposed in this paper. The proposed method is focused on the solution of cooperative multi-object tracking among multiple sensor nodes when an object leaves the view field of the tracking node. The main contributions of our proposed method are that: (1) the sensing model of a video sensor and Kalman filter is utilized to achieve optimal sensor selection. (2) Projective Invariants are employed to integrate information from the related nodes. The experimental results show that the proposed method is effective for resolving the problem of tracking relay.","PeriodicalId":214459,"journal":{"name":"2011 IEEE 13th International Workshop on Multimedia Signal Processing","volume":"51 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Cooperative multi-object tracking method for Wireless Video Sensor Networks\",\"authors\":\"Zheng Chu, L. Zhuo, Yingdi Zhao, Xiaoguang Li\",\"doi\":\"10.1109/MMSP.2011.6093796\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the enormous number and the limited energy of network nodes in the wireless video sensor networks (WVSN) environment, to fulfil the complicated tasks, multiple sensor nodes should collaborate with each other. A cooperative multi-object tracking method for Wireless Video Sensor Networks is proposed in this paper. The proposed method is focused on the solution of cooperative multi-object tracking among multiple sensor nodes when an object leaves the view field of the tracking node. The main contributions of our proposed method are that: (1) the sensing model of a video sensor and Kalman filter is utilized to achieve optimal sensor selection. (2) Projective Invariants are employed to integrate information from the related nodes. The experimental results show that the proposed method is effective for resolving the problem of tracking relay.\",\"PeriodicalId\":214459,\"journal\":{\"name\":\"2011 IEEE 13th International Workshop on Multimedia Signal Processing\",\"volume\":\"51 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 13th International Workshop on Multimedia Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMSP.2011.6093796\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 13th International Workshop on Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2011.6093796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cooperative multi-object tracking method for Wireless Video Sensor Networks
For the enormous number and the limited energy of network nodes in the wireless video sensor networks (WVSN) environment, to fulfil the complicated tasks, multiple sensor nodes should collaborate with each other. A cooperative multi-object tracking method for Wireless Video Sensor Networks is proposed in this paper. The proposed method is focused on the solution of cooperative multi-object tracking among multiple sensor nodes when an object leaves the view field of the tracking node. The main contributions of our proposed method are that: (1) the sensing model of a video sensor and Kalman filter is utilized to achieve optimal sensor selection. (2) Projective Invariants are employed to integrate information from the related nodes. The experimental results show that the proposed method is effective for resolving the problem of tracking relay.