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RI | Research | Projects | 3D Head Motion Recovery in Real Time |
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Feature-based
3D Head Tracking Mailing address: Associated center: VASC Associated lab/group: People
Image Analysis Consortium |
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Description | Personnel
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We develop a feature-based tracking method
to recover the full-motion (3 rotations and 3 translations) of the head using a
cylindrical model. We introduce the SIFT features as a universal matching technique
in tracking process. Tracking by detection approach can overcome a divergence
problem, which frequently occurs in previous work (Region-based optical
flow approach). Our system automatically generates view-based head model.
It contains regions of the facial features, such as eyebrows, eyes, nose, mouth
and also ears when they are visible. A set of SIFT features is stored and
updated for each reference pose while tracking sequences. These templates are
employed to rectify error accumulation and to avoid divergence in tracking. The
robustness of the proposed system is experimentally shown in video sequences
with occlusion and fast motion.
Examples:
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AVI Movie (xvid codec) |
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Personnel [Past Members] |
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Name |
Title |
Email Address |
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Postdoctoral Fellow |
jsjang@cs.cmu.edu |
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U.A. and |
tk@cs.cmu.edu |
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Publications |
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