V. R. Reddy, T. Chattopadhyay, Kingshuk Chakravarty, Aniruddha Sinha
{"title":"使用kinect从任意位置和姿势识别人","authors":"V. R. Reddy, T. Chattopadhyay, Kingshuk Chakravarty, Aniruddha Sinha","doi":"10.1145/2668332.2668359","DOIUrl":null,"url":null,"abstract":"In this paper authors have proposed a person identification method independent of his position with respect to the input sensor. The proposed method works for various postures or states namely, standing, sitting, walking. This method initially identifies the person's state and separate SVM based models are used for person identification (PI) for each of these three above mentioned states.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Person identification from arbitrary position and posture using kinect\",\"authors\":\"V. R. Reddy, T. Chattopadhyay, Kingshuk Chakravarty, Aniruddha Sinha\",\"doi\":\"10.1145/2668332.2668359\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper authors have proposed a person identification method independent of his position with respect to the input sensor. The proposed method works for various postures or states namely, standing, sitting, walking. This method initially identifies the person's state and separate SVM based models are used for person identification (PI) for each of these three above mentioned states.\",\"PeriodicalId\":223777,\"journal\":{\"name\":\"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2668332.2668359\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2668332.2668359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Person identification from arbitrary position and posture using kinect
In this paper authors have proposed a person identification method independent of his position with respect to the input sensor. The proposed method works for various postures or states namely, standing, sitting, walking. This method initially identifies the person's state and separate SVM based models are used for person identification (PI) for each of these three above mentioned states.