{"title":"基于三维深度数据的人体运动轨迹识别","authors":"Zheng Chang, Qing Shen, X. Ban, Jing Guo","doi":"10.3182/20140824-6-ZA-1003.00532","DOIUrl":null,"url":null,"abstract":"Abstract based on the traditional machine vision recognition technology about human body movement trajectory, the paper finds out the shortcomings of the traditional recognition technology. By combining the three - dimensional depth data, the three-dimensional motion history image and the invariant moments of the three - dimensional motion history image computed as the eigenvector of body movements, the paper applies the method to the machine vision of the human body movements trajectory. In detail, the paper describes the algorithm and realization scheme of the human body movements trajectory recognition based on the three-dimensional depth data. Finally, comparing with the results of the recognition experiment, we verify that the method of human body movement trajectory recognition technology based on the three-dimensional data has a more accurate recognition rate and a better robustness.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"51 1","pages":"12331-12336"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Recognition of Human Body Movements Trajectory Based on the Three-Dimensional Depth Data\",\"authors\":\"Zheng Chang, Qing Shen, X. Ban, Jing Guo\",\"doi\":\"10.3182/20140824-6-ZA-1003.00532\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract based on the traditional machine vision recognition technology about human body movement trajectory, the paper finds out the shortcomings of the traditional recognition technology. By combining the three - dimensional depth data, the three-dimensional motion history image and the invariant moments of the three - dimensional motion history image computed as the eigenvector of body movements, the paper applies the method to the machine vision of the human body movements trajectory. In detail, the paper describes the algorithm and realization scheme of the human body movements trajectory recognition based on the three-dimensional depth data. Finally, comparing with the results of the recognition experiment, we verify that the method of human body movement trajectory recognition technology based on the three-dimensional data has a more accurate recognition rate and a better robustness.\",\"PeriodicalId\":13260,\"journal\":{\"name\":\"IFAC Proceedings Volumes\",\"volume\":\"51 1\",\"pages\":\"12331-12336\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IFAC Proceedings Volumes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3182/20140824-6-ZA-1003.00532\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC Proceedings Volumes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3182/20140824-6-ZA-1003.00532","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition of Human Body Movements Trajectory Based on the Three-Dimensional Depth Data
Abstract based on the traditional machine vision recognition technology about human body movement trajectory, the paper finds out the shortcomings of the traditional recognition technology. By combining the three - dimensional depth data, the three-dimensional motion history image and the invariant moments of the three - dimensional motion history image computed as the eigenvector of body movements, the paper applies the method to the machine vision of the human body movements trajectory. In detail, the paper describes the algorithm and realization scheme of the human body movements trajectory recognition based on the three-dimensional depth data. Finally, comparing with the results of the recognition experiment, we verify that the method of human body movement trajectory recognition technology based on the three-dimensional data has a more accurate recognition rate and a better robustness.