TY - GEN
T1 - Multi-resolution 3D morphable models and its matching method
AU - Kang, Bong Nam
AU - Byun, Hyeran
AU - Kim, Daijin
PY - 2008
Y1 - 2008
N2 - The inverse compositional image alignment (ICIA) is known as an efficient matching method for 3D morphable models (3DMMs). However, it requires a long computation time since the 3D face models consist of a large number of vertices. Also, it requires to recompute the Hessian matrix using the visible vertices every iteration. For a fast and an efficient matching, we propose the efficient and accurate hierarchical ICIA (HICIA) matching method for 3DMMs. The proposed matching method requires multi-resolution 3D face models and the Gaussian image pyramid. The multi-resolution 3D face models are built by sub-sampling at the 2:1 sampling rate to construct the lower-resolution 3D face models. For more accurate matching, we use a twostage model parameter update that only updates the rigid and the texture parameters and then updates all parameters after the initial convergence. We present several experimental results to prove that the proposed method shows better performance than that of the conventional ICIA matching method.
AB - The inverse compositional image alignment (ICIA) is known as an efficient matching method for 3D morphable models (3DMMs). However, it requires a long computation time since the 3D face models consist of a large number of vertices. Also, it requires to recompute the Hessian matrix using the visible vertices every iteration. For a fast and an efficient matching, we propose the efficient and accurate hierarchical ICIA (HICIA) matching method for 3DMMs. The proposed matching method requires multi-resolution 3D face models and the Gaussian image pyramid. The multi-resolution 3D face models are built by sub-sampling at the 2:1 sampling rate to construct the lower-resolution 3D face models. For more accurate matching, we use a twostage model parameter update that only updates the rigid and the texture parameters and then updates all parameters after the initial convergence. We present several experimental results to prove that the proposed method shows better performance than that of the conventional ICIA matching method.
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U2 - 10.1109/icpr.2008.4760979
DO - 10.1109/icpr.2008.4760979
M3 - Conference contribution
AN - SCOPUS:77957905430
SN - 9781424421756
T3 - Proceedings - International Conference on Pattern Recognition
BT - 2008 19th International Conference on Pattern Recognition, ICPR 2008
PB - Institute of Electrical and Electronics Engineers Inc.
ER -