Abstract
Most existing techniques of foreground extracting work only in interactive mode. This paper introduces a novel algorithm of automatic foreground extraction for special object, and verifies its effectiveness with head shoulder images. The main contribution of our idea is to make the most use of the prior knowledge to constrain the processing of foreground extraction. For human head shoulder images, we first detect face and a few facial features, which helps to estimate an approximate mask covering the interesting region. The algorithm then extracts the hard edge of foreground from the specified area using an iterative graph cut method incorporated with an improved Gaussian Mixture Model. To generate accurate soft edges, a Bayes matting is applied. The whole process is fully automatic. Experimental results demonstrate that our algorithm is both robust and efficient.
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Wang, J., Ying, Y., Guo, Y., Peng, Q. (2006). Automatic Foreground Extraction of Head Shoulder Images. In: Nishita, T., Peng, Q., Seidel, HP. (eds) Advances in Computer Graphics. CGI 2006. Lecture Notes in Computer Science, vol 4035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11784203_33
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DOI: https://doi.org/10.1007/11784203_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35638-7
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