원문정보
초록
영어
This paper presents the methodology and performance of a statistical shape representation for automatic facial expression analysis in 3-D. The core of the method uses the statistical shape modelling technique with the deformable model-based surface matching process, which is capable of simulation and interpretation of 3-D human facial expressions. Using the proposed method, a 3-D face is represented by a low-dimensional shape space vector conveying information about face shape. Since the method relies only on the 3-D shape, it is inherently invariant to changes in the background, illumination, and viewing angle, which are the difficulties often suffered in 2-D facial expression analysis. Using 3-D static facial data from the BU-3DFE database as well as the 3-D dynamic facial expression database recently built by the authors in the ADSIP Research Centre, the paper also reports on the performance of the proposed facial expression representation. Furthermore, to demonstrate the effectiveness of the proposed facial expression representation, a comparison is made with human performance by involvi
목차
1. Introduction
2. Statistical Shape Model
2.1. Construction of Statistical Shape Model
2.2. Model Matching
3. 3-D Facial Expression Databases
3.1. BU-3DFE Database
3.2. ADSIP Database
3.3. Validation of ADSIP Database
4. Results of Facial Expression Recognition
4.1. Evaluation using BU-3DFE Database
4.2. Evaluation with ADSIP Database
5. Conclusions and Future Work
References