{"title":"基于张量分析的多视角步态识别","authors":"Caijuan Shi, Q. Ruan, Song Guo","doi":"10.1109/ICOSP.2012.6491796","DOIUrl":null,"url":null,"abstract":"In this paper, we have proposed a tensor analysis method for multi-view gait recognition. Gait Energy Image (GEI) is used for gait feature and then 4-order tensor is composed. Using a generalized singular value decomposition method-HOSVD, this tensor is decomposed to person subspace, series subspace, view subspace and feature subspace. In person subspace we finish the multi-view gait recognition. Lastly, we perform recognition by using a simple nearest neighbor rule. Experimental results on the widely used CASIA-B gait database demonstrate the effectiveness of the proposed method.","PeriodicalId":143331,"journal":{"name":"2012 IEEE 11th International Conference on Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multi-view gait recognition based on tensor analysis\",\"authors\":\"Caijuan Shi, Q. Ruan, Song Guo\",\"doi\":\"10.1109/ICOSP.2012.6491796\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we have proposed a tensor analysis method for multi-view gait recognition. Gait Energy Image (GEI) is used for gait feature and then 4-order tensor is composed. Using a generalized singular value decomposition method-HOSVD, this tensor is decomposed to person subspace, series subspace, view subspace and feature subspace. In person subspace we finish the multi-view gait recognition. Lastly, we perform recognition by using a simple nearest neighbor rule. Experimental results on the widely used CASIA-B gait database demonstrate the effectiveness of the proposed method.\",\"PeriodicalId\":143331,\"journal\":{\"name\":\"2012 IEEE 11th International Conference on Signal Processing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 11th International Conference on Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.2012.6491796\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 11th International Conference on Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2012.6491796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-view gait recognition based on tensor analysis
In this paper, we have proposed a tensor analysis method for multi-view gait recognition. Gait Energy Image (GEI) is used for gait feature and then 4-order tensor is composed. Using a generalized singular value decomposition method-HOSVD, this tensor is decomposed to person subspace, series subspace, view subspace and feature subspace. In person subspace we finish the multi-view gait recognition. Lastly, we perform recognition by using a simple nearest neighbor rule. Experimental results on the widely used CASIA-B gait database demonstrate the effectiveness of the proposed method.