Paper Info
Title
Real-Time Facial Feature Detection for Person Identification System
Abstract
In this paper, we present an approach to real- time facial feature detection. Facial regions are seg- mented using Gabor filter responses with M-style grid matching. M-style grid matching method has been shown more effective than Gabor bunch graph matching method in many aspects such as frontal face detection against expression, in-planeldepth ro- tation, and various illumination environments. In addition, this approach can be implemented with low computational complexity. The center positions of both eyes are detected, from the segmented face region, by iterative binary thresholding with per- fect contour tracing. Comparing with other pattern matching methods, it is shown that our scheme is faster and more effective eye detection method. Off- line simulation results using the test image set taken under office illumination (fluorescence) are over 99% successful segmentation rate of facial region (Face Detection Rate : FDR), and 99% effective eye center position detection rate of facial region (Eye position Detection Rate : EDR) We have implemented the real-time system on Pentium-III550MHz PC, and the system is capable of finding a pair of facial feature points on 240 by 320 images at 220ms per image. 97% of FDR, and 85% of EDR are real-time performance of the online system. The measured computational complexity is as low as about 32WMOPS.
Year
Venue
Keywords
2000
MVA
pattern matching,computational complexity,real time,face detection,graph matching,real time systems
Field
DocType
Citations 
Computer vision,Pattern recognition,Object-class detection,Computer science,Segmentation,Gabor filter,Matching (graph theory),Artificial intelligence,Thresholding,Face detection,Pattern matching,Standard test image
Conference
1
PageRank 
References 
Authors
0.40
2
4
Name
Order
Citations
PageRank
Sung-uk Lee1354.57
Yushin Cho2676.33
Seok-cheol Kee312913.94
Sang Ryong Kim414312.08