Scattered data interpolation in three or more variables
Mathematical methods in computer aided geometric design
Synthesizing realistic facial expressions from photographs
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
ACM Computing Surveys (CSUR)
A parametric model for human faces.
A parametric model for human faces.
A nonparametric skin color model for face detection from color images
PDCAT'04 Proceedings of the 5th international conference on Parallel and Distributed Computing: applications and Technologies
New eye contact correction using radial basis function for wide baseline videoconference system
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
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This paper presents an automatic and novel method to generate a realistic 3D face model from stereo images. Typically, an image-based 3D face modeling system is in need of human intervention in facial feature extraction stage. To remove this human intervention, we propose HT(Hue-Tint) skin color model for facial feature extraction. Based on the proposed chrominance model, we can detect facial region and extract facial feature positions. Subsequently, the facial features are adjusted by using edge information of the detected facial region along with the proportions of the face. Moreover, the proposed facial extraction method can effectively eliminate the epipolar constraints caused by using stereo vision approach. In order to produce a realistic 3D face model, we adopt RBF(Radial-Based Function) to deform the generic face model according to the detected facial feature points from stereo images. For deformation locality parameter of RBF is critical since it can have significant impact on the quality of deformation. Thus, we propose new parameter decision rule that is applicable to scattered data interpolation. It makes clusters of feature points to detect points under the influence of each width parameter. From the experiments, we can show the proposed approach efficiently detects facial feature points and produces a realistic 3D face model.