Abstract
Existing techniques for facial feature point detection from color images include template matching, facial geometry and symmetry analysis, mathematical morphology, luminance and chrominance analysis, and PCA. However, these techniques are plagued by poor performance in the presence of scale variations. In this paper, a hybrid technique is proposed that employs a combination of the above approaches along with curvature analysis of the intensity surface of the face image in order to provide a superior performance with reduced computational complexity, even in the presence of scale variations.
Original language | English (US) |
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Title of host publication | Proceedings - 5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 134-138 |
Number of pages | 5 |
Volume | 2002-January |
ISBN (Electronic) | 0769515371 |
DOIs | |
State | Published - 2002 |
Event | 5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002 - Santa Fe, United States Duration: Apr 7 2002 → Apr 9 2002 |
Other
Other | 5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002 |
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Country/Territory | United States |
City | Santa Fe |
Period | 4/7/02 → 4/9/02 |
Keywords
- Computational complexity
- Eyes
- Face detection
- Facial features
- Image analysis
- Image color analysis
- Image edge detection
- Nose
- Performance analysis
- Principal component analysis
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications