{"title":"基于线段的手持单目SLAM","authors":"Lilian Zhang, R. Koch","doi":"10.1109/IMVIP.2011.11","DOIUrl":null,"url":null,"abstract":"This paper presents an approach of visual SLAM using line segments as primitives. We choose Plucker lines to represent spatial lines and derive a novel fast line projection function based on the relationship between Pl̈ucker line and Plucker matrix. During normal SLAM procedure, the Near by Line Tracking (NLT) method is adopted to track lines and an Extended Kalman Filter (EKF) is used to predict and update the state of the camera and line landmarks. After each update step, a robust spatial line reconstruction algorithm is used to find new line landmarks and to add them into the map. The SLAM procedure is under supervision and when failure is detected, a recovery method based on the angle histogram of key frames is adopted to relocalize the camera and re-start the SLAM procedure. We demonstrate that our monocular SLAM system is robust to illumination change, partial occlusion and fast camera motion.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Hand-Held Monocular SLAM Based on Line Segments\",\"authors\":\"Lilian Zhang, R. Koch\",\"doi\":\"10.1109/IMVIP.2011.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an approach of visual SLAM using line segments as primitives. We choose Plucker lines to represent spatial lines and derive a novel fast line projection function based on the relationship between Pl̈ucker line and Plucker matrix. During normal SLAM procedure, the Near by Line Tracking (NLT) method is adopted to track lines and an Extended Kalman Filter (EKF) is used to predict and update the state of the camera and line landmarks. After each update step, a robust spatial line reconstruction algorithm is used to find new line landmarks and to add them into the map. The SLAM procedure is under supervision and when failure is detected, a recovery method based on the angle histogram of key frames is adopted to relocalize the camera and re-start the SLAM procedure. We demonstrate that our monocular SLAM system is robust to illumination change, partial occlusion and fast camera motion.\",\"PeriodicalId\":179414,\"journal\":{\"name\":\"2011 Irish Machine Vision and Image Processing Conference\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Irish Machine Vision and Image Processing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMVIP.2011.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Irish Machine Vision and Image Processing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMVIP.2011.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents an approach of visual SLAM using line segments as primitives. We choose Plucker lines to represent spatial lines and derive a novel fast line projection function based on the relationship between Pl̈ucker line and Plucker matrix. During normal SLAM procedure, the Near by Line Tracking (NLT) method is adopted to track lines and an Extended Kalman Filter (EKF) is used to predict and update the state of the camera and line landmarks. After each update step, a robust spatial line reconstruction algorithm is used to find new line landmarks and to add them into the map. The SLAM procedure is under supervision and when failure is detected, a recovery method based on the angle histogram of key frames is adopted to relocalize the camera and re-start the SLAM procedure. We demonstrate that our monocular SLAM system is robust to illumination change, partial occlusion and fast camera motion.