Effective use of color information for large scale face verification

Neurocomputing

Volumn 101, Issue , 2013, Pages 43-51

  Liu, Chengjun ^a  

^a University Heights   (United States)

Author keywords

Compact color image representation; Discriminant analysis; Effective color feature extraction; Face Recognition Grand Challenge (FRGC); New color model; New similarity measure; Pattern recognition

Indexed keywords

COLOR FEATURE EXTRACTION; COLOR IMAGE REPRESENTATION; COLOR MODELS; FACE RECOGNITION GRAND CHALLENGES; SIMILARITY MEASURE;

DISCRETE COSINE TRANSFORMS; DISCRIMINANT ANALYSIS; FACE RECOGNITION; INFORMATION USE; PATTERN RECOGNITION;

COLOR;

ALGORITHM; ARTICLE; CALCULATION; COLOR; DISCRIMINANT ANALYSIS; FACE PROFILE; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE QUALITY; MATHEMATICAL COMPUTING; PATTERN RECOGNITION; PRIORITY JOURNAL; PROCESS OPTIMIZATION; RECEIVER OPERATING CHARACTERISTIC;

EID: 84868623137     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.05.029     Document Type: Article

References (22)

1. Bishop C.M. Pattern Recognition and Machine Learning 2006, Springer.
2. Comon P. Independent component analysis, a new concept?. Signal Process. 1994, 36:287-314.
3. Finlayson G.D., Hordley S.D., Hubel P.M. Color by correlation. a simple, unifying framework for color constancy. IEEE Trans. Pattern Anal. Mach. Intell. 2001, 23(11):1209-1221.
4. Fukunaga K. Introduction to Statistical Pattern Recognition 1990, Academic Press. second ed.
5. Geusebroek J.M., van den Boomgaard R., Smeulders A.W.M., Geerts H. Color invariance. IEEE Trans. Pattern Anal. Mach. Intell. 2001, 23(12):1338-1350.
6. Gonzalez R.C., Woods R.E. Digital Image Processing 2008, Pearson Prentice Hall. third ed.
7. Hjelmas E., Low B.K. Face detection. a survey. Comput. Vision Image Understanding 2001, 83:236-274.
8. Karhunen J., Oja E., Wang L., Vigario R., Joutsensalo J. A class of neural networks for independent component analysis. IEEE Trans. Neural Networks 1997, 8(3):486-504.
9. J. Kittler, Y.P. Li, J. Matas, On matching scores for LDA-based face verification, in: The British Machine Vision Conference, University of Bristol, Bristol, UK, 11-14 September 2000, pp. 42-51.
10. Liu C. Enhanced independent component analysis and its application to content based face image retrieval. IEEE Trans. Syst. Man Cybern. Part B Cybern. 2004, 34(2):1117-1127.
11. Liu C. Capitalize on dimensionality increasing techniques for improving face recognition grand challenge performance. IEEE Trans. Pattern Anal. Mach. Intell. 2006, 28(5):725-737.
12. Liu C. The Bayes decision rule induced similarity measures. IEEE Trans. Pattern Anal. Mach. Intell. 2007, 29(6):1086-1090.
13. Liu C. Learning the uncorrelated, independent, and discriminating color spaces for face recognition. IEEE Trans. Inf. Forensics Secur. 2008, 3(2):213-222.
14. Liu C., Yang J. ICA color space for pattern recognition. IEEE Trans. Neural Networks 2009, 20(2):248-257.
15. Liu Z., Liu C. Fusion of the complementary discrete cosine features in the yiq color space for face recognition. Comput. Vision Image Understanding 2008, 111(3):249-262.
16. Liu Z., Liu C. Fusion of color, local spatial and global frequency information for face recognition. Pattern Recognition 2010, 43(8):2882-2890.
17. V.E. Neagoe, An optimum 2D color space for pattern recognition, in: Proceedings of the 2006 International Conference on Image Processing, Computer Vision, and Pattern Recognition, Las Vegas, NV, USA, June 26-29, 2006, pp. 526-532.
18. O'Toole A.J., Phillips P.J., Jiang F., Ayyad J., Penard N., Abdi H. Face recognition algorithms surpass humans matching faces across changes in illumination. IEEE Trans. Pattern Anal. Mach. Intell. 2007, 29(9):1642-1646.
19. P.J. Phillips, P.J. Flynn, T. Scruggs, K.W. Bowyer, J. Chang, K. Hoffman, J. Marques, J. Min, W. Worek, Overview of the face recognition grand challenge, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005.
20. Shih P., Liu C. Comparative assessment of content-based face image retrieval in different color spaces. Int. J. Pattern Recognition Artif. Intell. 2005, 19(7):873-893.
21. Smeulders A.W.M., Worring M., Santini S., Gupta A., Jain R. Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach. Intell. 2000, 22(12):1349-1380.
22. V. Struc, N. Pavesic, The corrected normalized correlation coefficient: a novel way of matching score calculation for LDA-based face verification, in: The Fifth International Conference on Fuzzy Systems and Knowledge Discovery, Jinan, Shandong, China, 18-20 October 2008, pp. 110-115.