Title:
AAM based Face Tracking with Temporal Matching and Face Segmentation
Authors:
Mingcai Zhou, Lin Liang, Jian Sun, Yangsheng Wang
Abstract:
Active Appearance Model (AAM) based face tracking has
advantages of accurate alignment, high efficiency, and
effectiveness for handling face deformation. However, AAM
suffers from the generalization problem and has difficulties
in images with cluttered backgrounds. In this paper, we in-
troduce two novel constraints into AAM fitting to address
the above problems. We first introduce a temporal matching
constraint in AAM fitting. In the proposed fitting scheme,
the temporal matching enforces an inter-frame local ap-
pearance constraint between frames. The resulting model
takes advantage of temporal matching's good generalizabil-
ity, but does not suffer from the mismatched points. To make
AAM more stable for cluttered backgrounds, we introduce a
color-based face segmentation as a soft constraint. Both
constraints effectively improve the AAM tracker's perfor-
mance, as demonstrated with experiments on various chal-
lenging real-world videos.
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