A video-based door monitoring system using local appearance-based face models

Computer Vision and Image Understanding

Volumn 114, Issue 5, 2010, Pages 596-608

  Ekenel, Hazim Kemal ^a   Stallkamp, Johannes ^a   Stiefelhagen, Rainer ^a,b  

^a KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

^b FRAUNHOFER IOSB   (Germany)

Author keywords

Discrete cosine transform; Door monitoring; Face detection; Face recognition from video; Feature tracking; Fusion

Indexed keywords

APPEARANCE BASED; APPLICATION SCENARIO; CLASSIFICATION DECISION; CONFIDENCE SCORE; FACE DETECTION; FACE MODELS; FACE RECOGNITION ALGORITHMS; FACIAL APPEARANCE; FACIAL FEATURE; FUSION; MONITORING SYSTEM; NON-COOPERATIVE; REAL TIME VIDEOS; RECOGNITION RATES; VIDEO FEATURES;

COSINE TRANSFORMS; DISCRETE COSINE TRANSFORMS; DOORS; SPEECH RECOGNITION;

FACE RECOGNITION;

EID: 77950945384     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2009.06.009     Document Type: Article

References (46)

1. Gross R. Face databases. Handbook of Face Recognition (2005), Springer
2. A. Lemieux, M. Parizeau, Experiments on eigenfaces robustness, in: Proceedings of the International Conference on Pattern Recognition, vol. 1, 2002, pp. 421-424.
3. Rentzeperis E., Stergiou A., Pnevmatikakis A., and Polymenakos L. Impact of face registration errors on recognition. Artificial Intelligence Applications and Innovations (AIAI06) (2006), Springer 187-194
4. Cognitec Systems GmbH. .
5. Cross Match Technologies. .
6. L-1 Identity Solutions. .
7. Ex-Sight. .
8. XID Technologies. http://www.xidtech.com/.
9. Viewdle. .
10. Riya. .
11. J. Stallkamp, H.K. Ekenel, R. Stiefelhagen, Video-based face recognition on real-world data, in: Proceedings of the International Conference on Computer Vision, 2007.
12. Turk M., and Pentland A. Eigenfaces for recognition. Journal of Cognitive Neuroscience 3 1 (1991) 71-86
13. Belhumeur P.N., Hespanha J.P., and Kriegman D.J. Eigenfaces vs. fisherfaces: recognition using class-specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19 7 (1997) 711-720
14. Georghiades A., Belhumeur P., and Kriegman D. From few to many: illumination cone models for face recognition under variable lighting and pose. IEEE Transactions on Pattern Analysis and Machine Intelligence 23 6 (2001) 643-660
15. Zhou S., Krueger V., and Chellappa R. Probabilistic recognition of human faces from video. Computer Vision and Image Understanding 91 1-2 (2003) 214-245
16. Lee K.C., Ho J., Yang M.H., and Kriegman D. Video-based face recognition using probabilistic appearance manifolds. Proceedings of the 2003 IEEE Computer Society Computer Vision and Pattern Recognition (2003), IEEE Computer Society 313-320
17. Liu X., and Chen T. Video-based face recognition using adaptive hidden markov models. Proceedings of the 2003 IEEE Computer Society International Conference on Computer Vision and Pattern Recognition (2003), IEEE Computer Society 340-345
18. O. Arandjelovic, A. Zisserman, Automatic face recognition for film character retrieval in feature-length films, in: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Washington, DC, USA, 2005, pp. 860-867.
19. Sivic J., Everingham M., and Zisserman A. Person spotting: video shot retrieval for face sets. In: Leow W.K., Lew M.S., Chua T.-S., Ma W.-Y., Chaisorn L., and Bakker E.M. (Eds). Proceedings of the International Conference on Image and Video Retrieval. Lecture Notes in Computer Science vol. 3568 (2005), Springer 226-236
20. Li F., and Wechsler H. Open set face recognition using transduction. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 11 (2005) 1686-1697
21. H.K. Ekenel, R. Stiefelhagen, Local appearance-based face recognition using discrete cosine transform, in: 13th European Signal Processing Conference (EUSIPCO 2005), 2005.
22. H.K. Ekenel, R. Stiefelhagen, Analysis of local appearance-based face recognition: Effects of feature selection and feature normalization, in: Conference on Computer Vision and Pattern Recognition Workshop 2006, 2006, p. 34.
23. M. Störring, H.J. Andersen, E. Granum, Skin colour detection under changing lighting conditions, in: H. Araujo, J. Dias (Eds.), 7th International Symposium on Intelligent Robotic Systems, 1999, pp. 187-195.
24. M. Störring, Computer vision and human skin colour, Ph.D. Thesis, Aalborg University, Denmark, August 2004.
25. B. Martinkauppi, M.N. Soriano, M.H. Laaksonen, Behavior of skin color under varying illumination seen by different cameras at different color spaces, in: M.A. Hunt (Ed.), SPIE Machine Vision in Industrial Inspection IX, vol. 4301, 2001.
26. Swain M.J., and Ballard D.H. Color indexing. International Journal of Computer Vision 7 1 (1991) 11-32
27. K. Schwerdt, J.L. Crowley, Robust face tracking using color, in: IEEE International Conference on Automatic Face and Gesture Recognition, 2000, p. 90.
28. Yoo T.-W., and Oh I.-S. A fast algorithm for tracking human faces based on chromatic histograms. Pattern Recognition Letters 20 (1999) 967-978
29. Canny J. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8 6 (1986) 679-698
30. Rosenfeld A., and Pfaltz J.L. Sequential operations in digital picture processing. Journal of the ACM 13 4 (1966) 471-494
31. Viola P., and Jones M.J. Robust real-time face detection. International Journal of Computer Vision 57 2 (2004) 137-154
32. Intel Corporation, Open source computer vision library (OpenCV), last visit: November 2006, 2006. .
33. Bar-Shalom Y., and Fortmann T.E. Tracking and Data Association (1988), Academic Press, New York
34. H.K. Ekenel, A robust face recognition algorithm for real-world applications, Ph.D. Thesis, Universität Karlsruhe (TH), Germany, 2009.
35. A.M. Martinez, R. Benavente, The AR face database, Technical Report 24, CVC, 1998.
36. Sim T., Baker S., and Bsat M. The cmu pose, illumination, and expression database. IEEE Transactions on Pattern Analysis and Machine Intelligence 25 12 (2003) 1615-1618
37. 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 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, Los Alamitos, CA, USA, 2005, pp. 947-954.
38. Lee K., Ho J., and Kriegman D. Acquiring linear subspaces for face recognition under variable lighting. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 5 (2005) 684-698
39. A. Nefian, A hidden markov model-based approach for face detection and recognition, Ph.D. Thesis, Georgia Institute of Technology, USA, 1999.
40. Moghaddam B., Jebara T., and Pentland A. Bayesian face recognition. Pattern Recognition 33 11 (2000) 1771-1782
41. R. Stiefelhagen, K. Bernardin, R.T.R.R. Bowers, M. Michel, J. Garofolo, The CLEAR 2007 evaluation, in: Proceedings of the International Evaluation Workshops CLEAR 2007 and RT 2007, 2007, pp. 3-34.
42. Snelick R., Uludag U., Mink A., Indovina M., and Jain A.K. Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 3 (2005) 450-455
43. Kittler J., Hatef M., Duin R.P.W., and Matas J. On combining classifiers. IEEE Transactions on Pattern Analysis and Machine Intelligence 20 3 (1998) 226-239
44. Dempster A., Laird N., and Rubin D. Maximum-likelihood from incomplete data via EM algorithm. Journal Royal Statistical Society, Series B 39 (1977) 1-38
45. G. Welch, G. Bishop, An introduction to the Kalman filter, in: SIGGRAPH, Course 08, 2001.
46. Huber P.J. Robust Statistics (1981), Wiley