{"title":"Multi-resolution vehicle detection using artificial vision","authors":"A. Broggi, Pietro Cerri, P. C. Antonello","doi":"10.1109/IVS.2004.1336400","DOIUrl":null,"url":null,"abstract":"This paper describes a vehicle detection system using a single camera. It is based on the search for areas with a high vertical symmetry in multi-resolution images; symmetry is computed using different sized boxes centered on all the columns of the interest areas. All the columns with high symmetry are analyzed to get the width of detected objects. Horizontal edges are examined to find the base of the vehicle in the individuated area. The aim is to find horizontal lines located below an area with sufficient amount of edges. The algorithm deletes all the bounding boxes which are too large, too small, or too far from the camera in order to decrease the number of false positives. All the results found in different interest areas are mixed together and the overlapping bounding boxes are localized and managed in order to delete false positives. The algorithm analyzes images on a frame by frame basis, without any temporal correlation.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"127","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Intelligent Vehicles Symposium, 2004","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2004.1336400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 127
Abstract
This paper describes a vehicle detection system using a single camera. It is based on the search for areas with a high vertical symmetry in multi-resolution images; symmetry is computed using different sized boxes centered on all the columns of the interest areas. All the columns with high symmetry are analyzed to get the width of detected objects. Horizontal edges are examined to find the base of the vehicle in the individuated area. The aim is to find horizontal lines located below an area with sufficient amount of edges. The algorithm deletes all the bounding boxes which are too large, too small, or too far from the camera in order to decrease the number of false positives. All the results found in different interest areas are mixed together and the overlapping bounding boxes are localized and managed in order to delete false positives. The algorithm analyzes images on a frame by frame basis, without any temporal correlation.