Xiaona Song, Bo Yang, Zhiquan Feng, Ting-xin Xu, Deliang Zhu, Yan Jiang
{"title":"基于粒子群优化的摄像机标定","authors":"Xiaona Song, Bo Yang, Zhiquan Feng, Ting-xin Xu, Deliang Zhu, Yan Jiang","doi":"10.1109/CISP.2009.5302889","DOIUrl":null,"url":null,"abstract":"A novel camera calibration approach based on Particle Swarm Optimization(PSO) is put forward in this paper. Firstly, we designed 35 sample points on the calibration box; Secondly, the 3D point and their corresponding 2D image coordi- nate of these sample points were obtained; In this approach, PSO algorithm was adopted to obtain the camera intrinsic parameters. Among the 35 sample points, 30 points were used for training, and other 5 points were mainly used to evaluate the effectiveness of camera calibration. The techniques presented in this paper have been implemented and tested with both synthetic and real data. Our experimental results show that the method can obtain satisfying calibration accuracy.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"552 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Camera Calibration Based on Particle Swarm Optimization\",\"authors\":\"Xiaona Song, Bo Yang, Zhiquan Feng, Ting-xin Xu, Deliang Zhu, Yan Jiang\",\"doi\":\"10.1109/CISP.2009.5302889\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel camera calibration approach based on Particle Swarm Optimization(PSO) is put forward in this paper. Firstly, we designed 35 sample points on the calibration box; Secondly, the 3D point and their corresponding 2D image coordi- nate of these sample points were obtained; In this approach, PSO algorithm was adopted to obtain the camera intrinsic parameters. Among the 35 sample points, 30 points were used for training, and other 5 points were mainly used to evaluate the effectiveness of camera calibration. The techniques presented in this paper have been implemented and tested with both synthetic and real data. Our experimental results show that the method can obtain satisfying calibration accuracy.\",\"PeriodicalId\":263281,\"journal\":{\"name\":\"2009 2nd International Congress on Image and Signal Processing\",\"volume\":\"552 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd International Congress on Image and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP.2009.5302889\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5302889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Camera Calibration Based on Particle Swarm Optimization
A novel camera calibration approach based on Particle Swarm Optimization(PSO) is put forward in this paper. Firstly, we designed 35 sample points on the calibration box; Secondly, the 3D point and their corresponding 2D image coordi- nate of these sample points were obtained; In this approach, PSO algorithm was adopted to obtain the camera intrinsic parameters. Among the 35 sample points, 30 points were used for training, and other 5 points were mainly used to evaluate the effectiveness of camera calibration. The techniques presented in this paper have been implemented and tested with both synthetic and real data. Our experimental results show that the method can obtain satisfying calibration accuracy.