Abstract:
An automatic face recognition system based on multiple facial features is described. Each facial feature is represented by a Gabor-based complex vector and is localized b...Show MoreMetadata
Abstract:
An automatic face recognition system based on multiple facial features is described. Each facial feature is represented by a Gabor-based complex vector and is localized by an automatic facial feature detection scheme. Two face recognition approaches, named two-layer nearest neighbor (TLNN) and modular nearest feature line (MNFL) respectively, are proposed. Both TLNN and MNFL are based on the multiple facial features detected for each image and their superiority in face recognition is demonstrated.
Published in: Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)
Date of Conference: 28-30 March 2000
Date Added to IEEE Xplore: 06 August 2002
Print ISBN:0-7695-0580-5
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Face Recognition ,
- Facial Features ,
- Multiple Facial Features ,
- Automatic Recognition ,
- Complex Vector ,
- Local Area ,
- Center Frequency ,
- Characteristic Area ,
- Taylor Expansion ,
- Face Images ,
- Recognition Performance ,
- Background Image ,
- Part Of Changes ,
- Image Point ,
- Global Search ,
- Diverse Kinds ,
- Projection Point ,
- Distance Vector ,
- Illumination Variations ,
- Complex Coefficients ,
- Query Image ,
- Gallery Images ,
- Nearest Neighbor Approach ,
- Gabor Filters ,
- Non-parametric Classification ,
- Smallest Distance ,
- Part Of The Image ,
- Face Processing ,
- Face Area ,
- Significant Variation In Expression
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Face Recognition ,
- Facial Features ,
- Multiple Facial Features ,
- Automatic Recognition ,
- Complex Vector ,
- Local Area ,
- Center Frequency ,
- Characteristic Area ,
- Taylor Expansion ,
- Face Images ,
- Recognition Performance ,
- Background Image ,
- Part Of Changes ,
- Image Point ,
- Global Search ,
- Diverse Kinds ,
- Projection Point ,
- Distance Vector ,
- Illumination Variations ,
- Complex Coefficients ,
- Query Image ,
- Gallery Images ,
- Nearest Neighbor Approach ,
- Gabor Filters ,
- Non-parametric Classification ,
- Smallest Distance ,
- Part Of The Image ,
- Face Processing ,
- Face Area ,
- Significant Variation In Expression
