Abstract
This paper describes an object detection method based on sample consensus. Real time frame difference was employed to get the candidate foreground pixels. Then, a joint background model storing samples of visible and thermal videos was constructed through training to verify the initial foreground. So false positives produced by frame difference were reassigned to background. There were in total four channels (red, green, blue and thermal) in the proposed joint sample consensus background model. Our method performs object detection and fusion of both sensors’ information simultaneously, which reduces the complexity of our method. Experimental results illustrate that the presented detection method can achieve accurate detection results.
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Han, G., Cai, X., Wang, J. (2012). Consensus-Based Detection Method for Visible and Thermal Videos. In: Liu, C., Wang, L., Yang, A. (eds) Information Computing and Applications. ICICA 2012. Communications in Computer and Information Science, vol 308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34041-3_16
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DOI: https://doi.org/10.1007/978-3-642-34041-3_16
Publisher Name: Springer, Berlin, Heidelberg
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