{"title":"基于静态摄像机的人体方位识别","authors":"S. Roy","doi":"10.1109/ICE-CCN.2013.6528612","DOIUrl":null,"url":null,"abstract":"Detection of orientation of a human being with respect to a static camera is an important problem in computer vision. This paper proposes a method for detection of orientation of a human being from four different orientations (e.g. front, side-left, side-right, back) with respect to a static camera. In the proposed method, extraction of features of a human being has been performed in terms of boundary description known as the signature. A template database of four different human orientations has been created. The extracted features of a testing sample have been compared with that stored in the template database and a dissimilarity value has been calculated. The classification has been performed using the dissimilarity value as a metric. The results obtained are encouraging.","PeriodicalId":286830,"journal":{"name":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On recognition of human orientation with respect to a static camera\",\"authors\":\"S. Roy\",\"doi\":\"10.1109/ICE-CCN.2013.6528612\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Detection of orientation of a human being with respect to a static camera is an important problem in computer vision. This paper proposes a method for detection of orientation of a human being from four different orientations (e.g. front, side-left, side-right, back) with respect to a static camera. In the proposed method, extraction of features of a human being has been performed in terms of boundary description known as the signature. A template database of four different human orientations has been created. The extracted features of a testing sample have been compared with that stored in the template database and a dissimilarity value has been calculated. The classification has been performed using the dissimilarity value as a metric. The results obtained are encouraging.\",\"PeriodicalId\":286830,\"journal\":{\"name\":\"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICE-CCN.2013.6528612\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICE-CCN.2013.6528612","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On recognition of human orientation with respect to a static camera
Detection of orientation of a human being with respect to a static camera is an important problem in computer vision. This paper proposes a method for detection of orientation of a human being from four different orientations (e.g. front, side-left, side-right, back) with respect to a static camera. In the proposed method, extraction of features of a human being has been performed in terms of boundary description known as the signature. A template database of four different human orientations has been created. The extracted features of a testing sample have been compared with that stored in the template database and a dissimilarity value has been calculated. The classification has been performed using the dissimilarity value as a metric. The results obtained are encouraging.