Abstract
In this paper, an efficient method for human facial expression recognition is presented. Our method includes two major techniques: spatially maximum occurrence model (SMOM), which is used to describe the different facial expressions; and elastic shape-texture matching (ESTM), which is used to compute the similarity between two images. The combination of these two techniques, namely the SMOM-ESTM method, is used to classify the facial expressions. With our approach, the recognition rate based on the AR database is 94.5%.
| Original language | English |
|---|---|
| Pages (from-to) | 786-793 |
| Number of pages | 8 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 5960 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Dec 2005 |
| Event | Visual Communications and Image Processing 2005 - Beijing, China Duration: 12 Jul 2005 → 15 Jul 2005 |
Keywords
- Elastic shape-texture matching
- Facial expression recognition
- Spatially maximum occurrence model
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Condensed Matter Physics
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