Densely tracking sequences of 3D face scans
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by
Huaxiong Ding, Liming Chen
2017
Abstract
3D face dense tracking aims to find dense inter-frame correspondences in a
sequence of 3D face scans and constitutes a powerful tool for many face
analysis tasks, e.g., 3D dynamic facial expression analysis. The majority of
the existing methods just fit a 3D face surface or model to a 3D target surface
without considering temporal information between frames. In this paper, we
propose a novel method for densely tracking sequences of 3D face scans, which
ex- tends the non-rigid ICP algorithm by adding a novel specific criterion for
temporal information. A novel fitting framework is presented for automatically
tracking a full sequence of 3D face scans. The results of experiments carried
out on the BU4D-FE database are promising, showing that the proposed algorithm
outperforms state-of-the-art algorithms for 3D face dense tracking.
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