{"title":"基于MACH和粒子滤波的行人自动检测与跟踪方法","authors":"Qiulei Han, Z. Yao","doi":"10.1109/NCIS.2011.84","DOIUrl":null,"url":null,"abstract":"This paper introduces a pedestrian detecting and tracking approach. Correlation filters present the composite properties which have been successively used in target detection. Particle filter are combined to locate the targets in real-time. Our contribution is proposing a general algorithm that is able to detect and track pedestrians in clutter environments. We also create a different view pedestrian dataset. Experiments show our algorithm is comparative when there is block and occlusion in tracking.","PeriodicalId":215517,"journal":{"name":"2011 International Conference on Network Computing and Information Security","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Automatic Pedestrian Detection and Tracking Method: Based on MACH and Particle Filter\",\"authors\":\"Qiulei Han, Z. Yao\",\"doi\":\"10.1109/NCIS.2011.84\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a pedestrian detecting and tracking approach. Correlation filters present the composite properties which have been successively used in target detection. Particle filter are combined to locate the targets in real-time. Our contribution is proposing a general algorithm that is able to detect and track pedestrians in clutter environments. We also create a different view pedestrian dataset. Experiments show our algorithm is comparative when there is block and occlusion in tracking.\",\"PeriodicalId\":215517,\"journal\":{\"name\":\"2011 International Conference on Network Computing and Information Security\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Network Computing and Information Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCIS.2011.84\",\"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 International Conference on Network Computing and Information Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCIS.2011.84","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Automatic Pedestrian Detection and Tracking Method: Based on MACH and Particle Filter
This paper introduces a pedestrian detecting and tracking approach. Correlation filters present the composite properties which have been successively used in target detection. Particle filter are combined to locate the targets in real-time. Our contribution is proposing a general algorithm that is able to detect and track pedestrians in clutter environments. We also create a different view pedestrian dataset. Experiments show our algorithm is comparative when there is block and occlusion in tracking.