{"title":"基于邻接矩阵的图像中人体识别对象表示","authors":"S. Saravanakumar, A. Vadivel","doi":"10.1109/ARTCom.2009.70","DOIUrl":null,"url":null,"abstract":"In this paper the human object present in images are identified. K-means clustering algorithm is used for segmenting the images and Connected Component Analysis is used as post-processing step. Initially, templates are created from human posture in idle and various angles. The adjacency matrix is constructed from objects and it is matched with templates. A similarity measure has been proposed for estimating the matching.","PeriodicalId":210885,"journal":{"name":"Advances in Recent Technologies in Communication and Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Adjacency Matrix Based Objects Representation for Human Identification in Images\",\"authors\":\"S. Saravanakumar, A. Vadivel\",\"doi\":\"10.1109/ARTCom.2009.70\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the human object present in images are identified. K-means clustering algorithm is used for segmenting the images and Connected Component Analysis is used as post-processing step. Initially, templates are created from human posture in idle and various angles. The adjacency matrix is constructed from objects and it is matched with templates. A similarity measure has been proposed for estimating the matching.\",\"PeriodicalId\":210885,\"journal\":{\"name\":\"Advances in Recent Technologies in Communication and Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Recent Technologies in Communication and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ARTCom.2009.70\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Recent Technologies in Communication and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARTCom.2009.70","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adjacency Matrix Based Objects Representation for Human Identification in Images
In this paper the human object present in images are identified. K-means clustering algorithm is used for segmenting the images and Connected Component Analysis is used as post-processing step. Initially, templates are created from human posture in idle and various angles. The adjacency matrix is constructed from objects and it is matched with templates. A similarity measure has been proposed for estimating the matching.
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