{"title":"改进人体动作识别的基于深度图像的目标分割方案","authors":"Sungjoo Park, U. Park, Dongchil Kim","doi":"10.23919/ELINFOCOM.2018.8330654","DOIUrl":null,"url":null,"abstract":"Human action recognition using the 3D camera for surveillance applications is a promising alternative approach to the conventional 2D camera based surveillance. We propose a depth image-based object segmentation scheme for improving human action recognition. Experimental results show that the average accuracy of the dangerous event detection is improved by about 15% when using the proposed object segmentation scheme.","PeriodicalId":413646,"journal":{"name":"2018 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"608 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Depth image-based object segmentation scheme for improving human action recognition\",\"authors\":\"Sungjoo Park, U. Park, Dongchil Kim\",\"doi\":\"10.23919/ELINFOCOM.2018.8330654\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Human action recognition using the 3D camera for surveillance applications is a promising alternative approach to the conventional 2D camera based surveillance. We propose a depth image-based object segmentation scheme for improving human action recognition. Experimental results show that the average accuracy of the dangerous event detection is improved by about 15% when using the proposed object segmentation scheme.\",\"PeriodicalId\":413646,\"journal\":{\"name\":\"2018 International Conference on Electronics, Information, and Communication (ICEIC)\",\"volume\":\"608 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Electronics, Information, and Communication (ICEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ELINFOCOM.2018.8330654\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Electronics, Information, and Communication (ICEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ELINFOCOM.2018.8330654","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Depth image-based object segmentation scheme for improving human action recognition
Human action recognition using the 3D camera for surveillance applications is a promising alternative approach to the conventional 2D camera based surveillance. We propose a depth image-based object segmentation scheme for improving human action recognition. Experimental results show that the average accuracy of the dangerous event detection is improved by about 15% when using the proposed object segmentation scheme.
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