Abstract
In this paper, we present an automatic and accurate pedestrian segmentation algorithm by incorporating pedestrian shape prior into the random walks segmentation algorithm. The random walks [1] algorithm requires user-specified labels to produce segmentation with each pixel assigned to a label, and it can provide satisfactory segmentation result with proper input labeled seeds. To take advantage of this interactive segmentation algorithm, we improve the random walks segmentation algorithm by incorporating prior shape information into the same optimization formulation. By using the human shape prior, we develop a fully automatic pedestrian image segmentation algorithm. Our experimental results demonstrate that the proposed algorithm significantly outperforms the previous segmentation methods in terms of pedestrian segmentation accuracy on a number of real images.
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Li, KC., Su, HR., Lai, SH. (2011). Pedestrian Image Segmentation via Shape-Prior Constrained Random Walks. In: Ho, YS. (eds) Advances in Image and Video Technology. PSIVT 2011. Lecture Notes in Computer Science, vol 7088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25346-1_20
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DOI: https://doi.org/10.1007/978-3-642-25346-1_20
Publisher Name: Springer, Berlin, Heidelberg
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