Adjusting shape parameters using model-based optical flow residuals

被引:17
作者
DeCarlo, D
Metaxas, D
机构
[1] Rutgers State Univ, Dept Comp Sci, Piscataway, NJ 08854 USA
[2] Rutgers State Univ, Ctr Cognit Sci, Piscataway, NJ 08854 USA
[3] Rutgers State Univ, Div Comp & Informat Sci, Piscataway, NJ 08854 USA
[4] Rutgers State Univ, Dept Bioengn, Piscataway, NJ 08854 USA
基金
美国国家科学基金会;
关键词
nonrigid shape and motion estimation; model-based optical flow; deformable models;
D O I
10.1109/TPAMI.2002.1008387
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a method for estimating the shape of a deformable model using the least-squares residuals from a model-based optical flow computation. This method is built on top of an estimation framework using optical flow and image features, where optical flow affects only the motion parameters of the model. Using the results of this computation, our new method adjusts all of the parameters so that the residuals from the flow computation are minimized. We present face tracking experiments that demonstrate that this method obtains a better estimate of shape compared to related frameworks.
引用
收藏
页码:814 / 823
页数:10
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