{"title":"从Kinect传感器提取平面特征","authors":"E. Bostanci, N. Kanwal, A. Clark","doi":"10.1109/CEEC.2012.6375388","DOIUrl":null,"url":null,"abstract":"An algorithm for finding planar features from a 3D point cloud by Kinect's depth sensor is described in this paper. The algorithm uses the explicit definition of a plane which allows storing only four parameters per plane rather than storing thousands of points. Extraction of multiple planes from the same set of points is prevented using a rejection mechanism. Parallelism is used for an average speed-up of 2.3:1. Details of the algorithm and results are given along with a discussion of how the calibration of the sensor affects the projections.","PeriodicalId":142286,"journal":{"name":"2012 4th Computer Science and Electronic Engineering Conference (CEEC)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Extracting planar features from Kinect sensor\",\"authors\":\"E. Bostanci, N. Kanwal, A. Clark\",\"doi\":\"10.1109/CEEC.2012.6375388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An algorithm for finding planar features from a 3D point cloud by Kinect's depth sensor is described in this paper. The algorithm uses the explicit definition of a plane which allows storing only four parameters per plane rather than storing thousands of points. Extraction of multiple planes from the same set of points is prevented using a rejection mechanism. Parallelism is used for an average speed-up of 2.3:1. Details of the algorithm and results are given along with a discussion of how the calibration of the sensor affects the projections.\",\"PeriodicalId\":142286,\"journal\":{\"name\":\"2012 4th Computer Science and Electronic Engineering Conference (CEEC)\",\"volume\":\"119 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 4th Computer Science and Electronic Engineering Conference (CEEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEEC.2012.6375388\",\"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 4th Computer Science and Electronic Engineering Conference (CEEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEEC.2012.6375388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An algorithm for finding planar features from a 3D point cloud by Kinect's depth sensor is described in this paper. The algorithm uses the explicit definition of a plane which allows storing only four parameters per plane rather than storing thousands of points. Extraction of multiple planes from the same set of points is prevented using a rejection mechanism. Parallelism is used for an average speed-up of 2.3:1. Details of the algorithm and results are given along with a discussion of how the calibration of the sensor affects the projections.
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