Gender Estimation using Single Exemplar of Frontal Facial Image per Person
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- 발행기관
- 보안공학연구지원센터(IJAST) 바로가기
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- 간행물
- International Journal of Advanced Science and Technology 바로가기
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- 통권
- Vol.40 (2012.03)바로가기
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- 페이지
- pp.1-18
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A206688
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- So far, several methods have been proposed for gender estimation based on training processes, using several images per person. In this paper, we introduce a new gender estimation method based on single image per person. First, reference images, called general faces, are constructed by averaging male and female images in the dataset respectively. Then, important face features such as eyes and mouth are highlighted by Wavelet fusion of Sobel Detector, and Laplacian of Gaussian images. The highlighted image is segmented into seven partitions. In the obtained image, those segments like eyes and eyebrows with more variations (containing more information) play more significant role in the gender estimation process. Weight of each segment is proportional to its entropy. Finally, DCT coefficients of each segment in the input facial image are compared to their counterparts in general faces. Considering weight of each segment and fuzzy rule sets, the input image is assigned to the closest class. The proposed method is evaluated on FERET and AR databases. Experimental results show that the proposed method is tolerant of variations such as facial expression, occlusion, and rotation.
목차
Abstract
1. Introduction
2. Related Work
3. The Proposed Gender Estimation Algorithm
3.1. Image Datasets
3.2. General Face Construction
3.3. Image Partitioning
3.4. Face Features Highlighting
3.5. Image Entropy
3.6. Discrete Cosine Transform
3.7. Distance Measures
3.8. Fuzzy System
4. Experimental Results
4.1. Distance Measures Study
4.2. Number of Images Effect
4.3. Fuzzy Logic Effect
4.4. Performance Evaluation Using Different Datasets
4.5. Performance Evaluation Using Non-frontal Facial Images
4.6. Performance Evaluation with Occulted Images
4.7. Performance Evaluation Using an Ethnic Dataset
4.8. Comparison with Related Works
5. Conclusion and Future Work
Acknowledgements
References
키워드
Gender estimation; Single face image; Image partitioning; Image entropy.저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJAST) [Science & Engineering Research Support Center, Republic of Korea(IJAST)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Advanced Science and Technology
- 간기
- 월간
- pISSN
- 2005-4238
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Advanced Science and Technology Vol.40
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