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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.14 No.3
- 발행연도
- 2014.9
- 수록면
- 162 - 170 (9page)
이용수
초록· 키워드
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Appearance-based subspace models such as eigenfaces have been widely recognized as one of the most successful approaches to face recognition and tracking. The success of eigenfaces mainly has its origins in the benefits offered by principal component analysis (PCA), the representational power of the underlying generative process for high-dimensional noisy facial image data. The sparse extension of PCA (SPCA) has recently received significant attention in the research community. SPCA functions by imposing sparseness constraints on the eigenvectors, a technique that has been shown to yield more robust solutions in many applications. However, when SPCA is applied to facial images, the time and space complexity of PCA learning becomes a critical issue (e.g., real-time tracking). In this paper, we propose a very fast and scalable greedy forward selection algorithm for SPCA. Unlike a recent semidefinite program-relaxation method that suffers from complex optimization, our approach can process several thousands of data dimensions in reasonable time with little accuracy loss. The effectiveness of our proposed method was demonstrated on real-world face recognition and tracking datasets.
목차
Abstract
1. Introduction
2. Background and Previous Work
3. Greedy Learning of Sparse Eigenfaces
4. Experimental Results
5. Conclusions
References
참고문헌 (19)
참고문헌 신청
1. [학술지(정기간행물)] - K. Pearson / 1901 / LIII. On lines and planes of closest fit to systems of points in space / Philosophical Magazine Series 6 2 (11) : 559 ~ 572
2. [학술지(정기간행물)] - H. Hotelling / 1933 / Analysis of a complex of statistical variables into principal components / Journal of Educational Psychology 24 (6) : 417 ~ 441
3. [단행본] - I. T. Jolliffe / 1986 / Principal Component Analysis / Springer-Verlag
4. [학술지(정기간행물)] - L. Sirovich / 1987 / Low-dimensional procedure for the characterization of human faces / Journal of the Optical Society of America A : Optics and Image Science 4 (3) : 519 ~ 524
5. [학술지(정기간행물)] - M. Kirby / 1990 / Application of the Karhunen-Loeve procedure for the characterization of human faces / IEEE Transactions on Pattern analysis and Machine Intelligence 12 (1) : 103 ~ 108
2. [학술지(정기간행물)] - H. Hotelling / 1933 / Analysis of a complex of statistical variables into principal components / Journal of Educational Psychology 24 (6) : 417 ~ 441
3. [단행본] - I. T. Jolliffe / 1986 / Principal Component Analysis / Springer-Verlag
4. [학술지(정기간행물)] - L. Sirovich / 1987 / Low-dimensional procedure for the characterization of human faces / Journal of the Optical Society of America A : Optics and Image Science 4 (3) : 519 ~ 524
5. [학술지(정기간행물)] - M. Kirby / 1990 / Application of the Karhunen-Loeve procedure for the characterization of human faces / IEEE Transactions on Pattern analysis and Machine Intelligence 12 (1) : 103 ~ 108
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UCI(KEPA) : I410-ECN-0101-2015-004-002822838