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  • 标题:A Novel Approach for On-road Vehicle Detection and Tracking
  • 本地全文:下载
  • 作者:Ilyas EL JAAFARI ; Mohamed EL ANSARI ; Lahcen KOUTTI
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2016
  • 卷号:7
  • 期号:1
  • DOI:10.14569/IJACSA.2016.070181
  • 出版社:Science and Information Society (SAI)
  • 摘要:On the basis of a necessary development of the road safety, vision-based vehicle detection techniques have gained an important amount of attention. This work presents a novel vehicle detection and tracking approach, and structured based on a vehicle detection process starting from, images or video data acquired from sensors installed on board of the vehicle, to vehicle detection and tracking. The features of the vehicle are extracted by the proposed GIST image processing algorithm, and recognized by the state-of-art Support Vectors Machine classifier. The tracking process was performed based on edge features matching approach. The Kalman filter was used to correct the measurements. Extensive experiments were carried out on real image data validate that it is promising to employ the proposed approach for on road vehicle detection and tracking.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Vehicle detection; Vehicle tracking; GIST; SVM; Edge features; Kalman filter
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