In this paper, we propose a marker-less motion capture method for a human face. We detect the movement of a face as the deformation from the initial pose to other poses. In such cases, the non-rigid registration algorithms are commonly used to detect the movement of an object. However, since the features of the movement of a face vary in each facial part, it complicates the registration problem. In our method, we recognize the facial parts by using Random Forest algorithm to be simplified to solve the registration problem. Then, we classify the facial parts into five types: nose, mouth, eye, cheek and obstacle. And we define the feature vector of each point of the face by using Fast Point Feature Histograms and a normalized position. We train the Random Forest based on the feature vector to recognize the facial parts from an arbitrary point set data. After the recognition of the facial parts, we detect the movement of the each part by using a non-rigid registration algorithm. Finally, we combine the translations of the each point as the deformation of the face by using the deformation technique based on a Radial Basis Function. In our results, we show that the proposed method enable us to detect the motion of the face more accurately.
|Number of pages
|Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering
|Published - Nov 2013
All Science Journal Classification (ASJC) codes
- Mechanical Engineering