Abstract
In recent years, the detection accuracy has significantly improved under various conditions using sophisticated methods. However, these methods require a great deal of computational cost, and have difficulty in real-time applications. In this paper, we propose a real-time system for object detection in outdoor environments using a graphics processing unit (GPU). We implement two algorithms on a GPU: adaptive background model, and margined sign correlation. These algorithms can robustly detect moving objects and remove shadow regions. Experimental results demonstrate the real-time performance of the proposed system.
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Yamamoto, A., Iwai, Y. (2010). Real-Time Object Detection with Adaptive Background Model and Margined Sign Correlation. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12297-2_7
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DOI: https://doi.org/10.1007/978-3-642-12297-2_7
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