{"title":"移动机器人检测与跟踪学习系统","authors":"Sonda Bousnina, B. Ammar, N. Baklouti, A. Alimi","doi":"10.1109/ICCITECHNOL.2012.6285831","DOIUrl":null,"url":null,"abstract":"Visual detection and tracking is an important and challenging problem in the area of computer vision. Numerous researches have been undergoing. In this paper, we present a target-tracking system specific for mobile robots. We used in our system the Gabor filter to extract the robot features. Robot detection is based on the Support Vector Machine (SVM) classifier. Once the detection is accomplished, the Kalman filter is employed to track the detected robot. Experimental results have been extracted for a set of video sequences with the moving robot at different positions and with a variation of backgrounds.","PeriodicalId":435718,"journal":{"name":"2012 International Conference on Communications and Information Technology (ICCIT)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Learning system for mobile robot detection and tracking\",\"authors\":\"Sonda Bousnina, B. Ammar, N. Baklouti, A. Alimi\",\"doi\":\"10.1109/ICCITECHNOL.2012.6285831\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Visual detection and tracking is an important and challenging problem in the area of computer vision. Numerous researches have been undergoing. In this paper, we present a target-tracking system specific for mobile robots. We used in our system the Gabor filter to extract the robot features. Robot detection is based on the Support Vector Machine (SVM) classifier. Once the detection is accomplished, the Kalman filter is employed to track the detected robot. Experimental results have been extracted for a set of video sequences with the moving robot at different positions and with a variation of backgrounds.\",\"PeriodicalId\":435718,\"journal\":{\"name\":\"2012 International Conference on Communications and Information Technology (ICCIT)\",\"volume\":\"162 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Communications and Information Technology (ICCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCITECHNOL.2012.6285831\",\"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 International Conference on Communications and Information Technology (ICCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCITECHNOL.2012.6285831","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Learning system for mobile robot detection and tracking
Visual detection and tracking is an important and challenging problem in the area of computer vision. Numerous researches have been undergoing. In this paper, we present a target-tracking system specific for mobile robots. We used in our system the Gabor filter to extract the robot features. Robot detection is based on the Support Vector Machine (SVM) classifier. Once the detection is accomplished, the Kalman filter is employed to track the detected robot. Experimental results have been extracted for a set of video sequences with the moving robot at different positions and with a variation of backgrounds.