Face recognition using asymmetric faces

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3072, Issue , 2004, Pages 162-168

  Gutta, Srinivas ^a   Wechsler, Harry ^b  

^a PHILIPS RESEARCH LABORATORIES   (Netherlands)

^b Krasnow Institute for Advanced Study   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA ACQUISITION; EXPERT SYSTEMS; IMAGE PROCESSING; OPTICAL TESTING; RADIAL BASIS FUNCTION NETWORKS;

ACQUISITION PROCESS; INHERENT VARIABILITY; K FOLD CROSS VALIDATIONS; MIRROR IMAGES; MIXTURE OF EXPERTS; RADIAL BASIS FUNCTIONS; RECOGNITION ABILITIES; RECOGNITION ENGINES;

FACE RECOGNITION;

EID: 35048857057     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-25948-0_23     Document Type: Article

References (11)

1. Gutta, S., Philomin, V., and Trajkovic, M.: An Investigation into the use of Partial Faces for Face Recognition, 5th International Conference on Face and Gesture Recognition (FGR). (2002) 33-38, Washington D.C., USA.
2. Gutta, S. and Wechsler, H.: Analysis of Partial-Faces for Face Recognition, 10th Int. Conf. on Computer Analysis of Images and Patterns (CAIP). (2003) Groningen, The Netherlands.
3. Liu, Y., Schmidt, K. L. Cohn, J. F. and Weaver, R. L.: Facial Asymmetry Quantification for Expression Invariant Human Identification, 16th Int. Conf. on Pattern Recognition, (ICPR) (2002), Quebec-City, Canada.
4. Thornhill, R. and Gangestad, S. W.: Facial Attractiveness, Trans. In Cognitive Sciences, 3(12) (1999) 452-460.
5. Richardson, C., Bowers, K. D., Bauer, R. M., Heilman, K. M., and Leonard, C. M.: Digitizing the Moving face During Dynamic Displays of Emotion, Neuropsychologia, 38(7) (2000) 1028-1039.
6. O'Toole, A.: The Perception of Face Gender: The Role of Stimulus Structure in Recognition and Classification, Memory and Cognition, 26(1) (1998) 146-160.
7. Martinez, A. M.: Recognizing Imprecisely Localized, Partially Occluded and Expression Variant Faces from a Single Sample per Class, IEEE Trans. on Pattern Analysis and Machine Intelligence, 24(6) (2002) 748-763.
8. Lippmann, R.P., Ng, K.: A Comparative Study of the Practical Characteristic of Neural Networks and Pattern Classifiers, MIT Lincoln Labs. Tech. Report 894 (1991).
9. Gutta, S., Wechsler, H.: Face Recognition using Hybrid Classifiers, Int. J. Pattern Recognition. 30(4) (1997) 539-553.
10. Colmenarez, A., Frey, B., Huang, T. S.: Detection and Tracking of Faces and Facial Features, in Proc. of International Conference on Image Processing. (1999) 268-272, Kobe, Japan.
11. Weiss, S.M., Kulikowski, C.A.: Computer Systems That Learn, Morgan Kaufmann, San Francisco (1991).