Adaptive Moving Cast Shadow Detection

نویسندگان

  • Guizhi Li
  • Lei Qin
  • Qingming Huang
چکیده

Moving object detection is an important task in real-time video surveillance. However, in real scenario, moving cast shadows associated with moving objects may also be detected, making moving cast shadow detection a challenge for video surveillance. In this paper, we propose an adaptive shadow detection method based on the cast shadow model. The method combines ratio edge and ratio brightness, and reduces computation complexity by the cascading algorithm. It calculates the difference of ratio edge between the shadow region and the background according to the invariability of the ratio edge of object in different light. Experimental results show that our approach outperforms existing methods.

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تاریخ انتشار 2011