{"title":"Vision-based real-time pedestrian detection for autonomous vehicle","authors":"Liu Xin, Dai Bin, He Hangen","doi":"10.1109/ICVES.2007.4456404","DOIUrl":null,"url":null,"abstract":"TMs paper presents a real-time single-frame pedestrian detection approach. Combining efficient interesting regions selection and proper SVM classifier, the method is applicable to the autonomous vehicles running on urban roads. Experiment results with test dataset extracted from real driving on urban roads are presented to illustrate the performance of this approach.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Vehicular Electronics and Safety","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVES.2007.4456404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
TMs paper presents a real-time single-frame pedestrian detection approach. Combining efficient interesting regions selection and proper SVM classifier, the method is applicable to the autonomous vehicles running on urban roads. Experiment results with test dataset extracted from real driving on urban roads are presented to illustrate the performance of this approach.
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