Jong-Ho Choi, Kang-Ho Lee, Kuk-Chan Cha, Jun-Sik Kwon, Dong-Wook Kim, Ho-Keun Song
{"title":"Vehicle Tracking using Template Matching based on Feature Points","authors":"Jong-Ho Choi, Kang-Ho Lee, Kuk-Chan Cha, Jun-Sik Kwon, Dong-Wook Kim, Ho-Keun Song","doi":"10.1109/IRI.2006.252477","DOIUrl":null,"url":null,"abstract":"We propose a new vehicle tracking system which can detect and monitor vehicles as they break traffic lane rules. Our proposed tracking scheme is based on characteristics of both traffic scene and vehicle. These include: background information, local position, and the size of a moving vehicle. The initial size and position of the vehicle are obtained using a 4-directional contour tracking method. The object contour is made less sensitive to luminosity changes by incorporating a frame differencing operation. Each vehicle can be described with four feature points. The template region is estimated by means of a minimum distance approach with respect to center position. Our experimental results confirm that extraction of feature points from each frame of the scene improves the efficiency of vehicle tracking systems. Furthermore, adjustment of the vehicle region with matched points of template resolves the previous problem of occlusion","PeriodicalId":402255,"journal":{"name":"2006 IEEE International Conference on Information Reuse & Integration","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE International Conference on Information Reuse & Integration","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRI.2006.252477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
We propose a new vehicle tracking system which can detect and monitor vehicles as they break traffic lane rules. Our proposed tracking scheme is based on characteristics of both traffic scene and vehicle. These include: background information, local position, and the size of a moving vehicle. The initial size and position of the vehicle are obtained using a 4-directional contour tracking method. The object contour is made less sensitive to luminosity changes by incorporating a frame differencing operation. Each vehicle can be described with four feature points. The template region is estimated by means of a minimum distance approach with respect to center position. Our experimental results confirm that extraction of feature points from each frame of the scene improves the efficiency of vehicle tracking systems. Furthermore, adjustment of the vehicle region with matched points of template resolves the previous problem of occlusion