{"title":"基于模糊推理背景差结合二次搜索的Camshift自动跟踪算法","authors":"Xiao Gang, Chen Yong, Chen Jiu-jun, Gao Fei","doi":"10.1109/EDT.2010.5496634","DOIUrl":null,"url":null,"abstract":"In order to overcome the shortcoming that traditional Camshift needs artificial orientation during tracking, this paper proposes a new approach of Camshift tracking algorithm based on fuzzy inference background difference. In this paper, the object contour extracted by background difference rather than artificial selection, is used as initial search window so as to realize automatic Camshift tracking. Meanwhile, to avoid object divergence and object losing when the object moves too quickly, twice Camshift searching is combined with background difference to enlarge the search window automatically to ensure consistent targeting. Furthermore, this paper also introduces contour marking and multiple Camshift trackers to implement successful multi-object tracking. Methods mentioned above prove themselves efficient and automatic in tracking one or more moving fishes during the experiments.","PeriodicalId":325767,"journal":{"name":"2010 International Conference on E-Health Networking Digital Ecosystems and Technologies (EDT)","volume":"13 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Automatic Camshift tracking algorithm based on fuzzy inference background difference combining with twice searching\",\"authors\":\"Xiao Gang, Chen Yong, Chen Jiu-jun, Gao Fei\",\"doi\":\"10.1109/EDT.2010.5496634\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to overcome the shortcoming that traditional Camshift needs artificial orientation during tracking, this paper proposes a new approach of Camshift tracking algorithm based on fuzzy inference background difference. In this paper, the object contour extracted by background difference rather than artificial selection, is used as initial search window so as to realize automatic Camshift tracking. Meanwhile, to avoid object divergence and object losing when the object moves too quickly, twice Camshift searching is combined with background difference to enlarge the search window automatically to ensure consistent targeting. Furthermore, this paper also introduces contour marking and multiple Camshift trackers to implement successful multi-object tracking. Methods mentioned above prove themselves efficient and automatic in tracking one or more moving fishes during the experiments.\",\"PeriodicalId\":325767,\"journal\":{\"name\":\"2010 International Conference on E-Health Networking Digital Ecosystems and Technologies (EDT)\",\"volume\":\"13 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on E-Health Networking Digital Ecosystems and Technologies (EDT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDT.2010.5496634\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on E-Health Networking Digital Ecosystems and Technologies (EDT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDT.2010.5496634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Camshift tracking algorithm based on fuzzy inference background difference combining with twice searching
In order to overcome the shortcoming that traditional Camshift needs artificial orientation during tracking, this paper proposes a new approach of Camshift tracking algorithm based on fuzzy inference background difference. In this paper, the object contour extracted by background difference rather than artificial selection, is used as initial search window so as to realize automatic Camshift tracking. Meanwhile, to avoid object divergence and object losing when the object moves too quickly, twice Camshift searching is combined with background difference to enlarge the search window automatically to ensure consistent targeting. Furthermore, this paper also introduces contour marking and multiple Camshift trackers to implement successful multi-object tracking. Methods mentioned above prove themselves efficient and automatic in tracking one or more moving fishes during the experiments.