Probabilistic Visual Learning for Object Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time face pose tracking and facial expression synthesizing for the animation of 3D avatar
Edutainment'07 Proceedings of the 2nd international conference on Technologies for e-learning and digital entertainment
A robust 3d face pose estimation and facial expression control for vision-based animation
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Image-Based 3d face modeling from stereo images
ICCSA'06 Proceedings of the 6th international conference on Computational Science and Its Applications - Volume Part I
Hi-index | 0.00 |
This paper presents a novel approach to extract face and facial feature points from color image automatically based on a nonparametric skin color model. Most of introduced skin color models for face detection have lack of robustness for varying lighting conditions and need extra work to reduce such problem. To resolve the limitation of current skin color model, we utilize the Hue-Tint chrominance model and represent the skin chrominance distribution as a linear equation. Thus, the facial color distribution is simply described as a combination of the maximum and minimum values of Hue and Tint components. The decision rule to detect skin region is simplified by measuring the distance between the skin chrominance distribution function and measured input chrominance. In order to extract facial feature points defined by MPEG-4, the minimal facial feature positions detected by the skin color model are subsequently adjusted by using edge information from the detected facial region along with the proportions of the face. The experiments show that the proposed method guarantees fast and exact processing for face and facial feature point generation and is robust to various lighting conditions and input images.