Hao Pang, Jiping Li, Jianjun Peng, Xin Zhong, Xiangyue Cai
{"title":"基于单个kinect的个性化全身重建","authors":"Hao Pang, Jiping Li, Jianjun Peng, Xin Zhong, Xiangyue Cai","doi":"10.1109/CISP.2015.7408021","DOIUrl":null,"url":null,"abstract":"To build 3D personalized human body geometry in virtual scenes, this paper presents a full human body reconstruction method based on single Kinect. This method captures three top-down human point clouds firstly and uses ICP to find the corresponding points between the point clouds. A personalized full human body point cloud is generated after point cloud fusion and down-sampling. Finally, the 3D human geometry is constructed by triangulation. The experimental results demonstrate the method feasibility.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Personalized full-body reconstruction based on single kinect\",\"authors\":\"Hao Pang, Jiping Li, Jianjun Peng, Xin Zhong, Xiangyue Cai\",\"doi\":\"10.1109/CISP.2015.7408021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To build 3D personalized human body geometry in virtual scenes, this paper presents a full human body reconstruction method based on single Kinect. This method captures three top-down human point clouds firstly and uses ICP to find the corresponding points between the point clouds. A personalized full human body point cloud is generated after point cloud fusion and down-sampling. Finally, the 3D human geometry is constructed by triangulation. The experimental results demonstrate the method feasibility.\",\"PeriodicalId\":167631,\"journal\":{\"name\":\"2015 8th International Congress on Image and Signal Processing (CISP)\",\"volume\":\"88 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 8th International Congress on Image and Signal Processing (CISP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP.2015.7408021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 8th International Congress on Image and Signal Processing (CISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2015.7408021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Personalized full-body reconstruction based on single kinect
To build 3D personalized human body geometry in virtual scenes, this paper presents a full human body reconstruction method based on single Kinect. This method captures three top-down human point clouds firstly and uses ICP to find the corresponding points between the point clouds. A personalized full human body point cloud is generated after point cloud fusion and down-sampling. Finally, the 3D human geometry is constructed by triangulation. The experimental results demonstrate the method feasibility.