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- W2014799021 abstract "This paper describes a robust 3D human face reconstruction approach by consumer binocular-stereo cameras. It aims to handle the ambiguity due to the captured noisy or distorted stereo images and the textureless nature of human face. First, seven facial feature points are extracted to deform a generic 3D face for initialization. A novel two-pass seed searching algorithm is then employed to deliver a set of sparse seeds. Also proposed is the seed outlier detection algorithm by using polynomial curves to introduce the smoothness prior. The resulting seeds significantly reduce the ambiguity, and propagate to remaining pixels using a modified seed growing strategy. The discussion also addresses polynomial curve fitting based disparity map denoising, stereo refinement and multibase-line matching for epipolar misalignment. They allow us to produce dense and detail preserving face models despite the low quality of image capture with consumer cameras. Both qualitative and quantitative evaluations demonstrate the state-of-the-art performance of our approach, and the accuracy is comparable to some active systems. Our approach can also deal with large facial expressions." @default.
- W2014799021 created "2016-06-24" @default.
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- W2014799021 date "2012-12-02" @default.
- W2014799021 modified "2023-09-23" @default.
- W2014799021 title "Robust 3D human face reconstruction by consumer binocular-stereo cameras" @default.
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- W2014799021 doi "https://doi.org/10.1145/2407516.2407580" @default.
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