3D Vehicle Extraction and Tracking from Multiple Viewpoints for Traffic Monitoring by using Probability Fusion Map

• Autores: Zhencheng Hu, Chenhao Wang, Keiichi Uchimura
• Localización: ELCVIA. Electronic letters on computer vision and image analysis, ISSN-e 1577-5097, Vol. 7, Nº. Extra 2, 2008 (Ejemplar dedicado a: Special Issue on Computational Modelling of Objects Represented in Images), págs. 110-119
• Idioma: inglés
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• Resumen

  • This paper presents a novel solution of vehicle occlusion and 3D measurement for traffic monitoring bydata fusion from multiple stationary cameras. Comparing with single camera based conventional methods intraffic monitoring, our approach fuses video data from different viewpoints into a common probability fusionmap (PFM) and extracts targets. The proposed PFM concept is efficient to handle and fuse data in orderto estimate the probability of vehicle appearance, which is verified to be more reliable than single camerasolution by real outdoor experiments. An AMF based shadowing modeling algorithm is also proposed inthis paper in order to remove shadows on the road area and extract the proper vehicle regions.