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Hair plays an important role in human appearance. However, hair segmentation is still a challenging problem partially due to the lack of an effective model to handle its arbitrary shape variations. In this paper, we present a part-based model robust to hair shape and environment variations. The key idea of our method is to identify local parts by promoting the effectiveness of the part-based model...
We describe a robust feature descriptor called soft ordinal spatial intensity distribution (soft OSID) that is invariant to any monotonically increasing brightness changes. In traditional histogram-based feature descriptors, each pixel is explicitly assigned to a single histogram bin, making them not robust to image deformations and appearance changes. In this paper, we present a feature descriptor...
Object tracking methods based on stereo cameras, which provide both color and depth data at each pixel, find advantage in separating objects from each other and from background, determining the 3D size and location of objects, and modeling object shape. However, stereo tracking methods to date sometimes fail due to depth image noise, and discard much useful appearance information. We propose augmenting...
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