[1]
|
P. Viola and M. Jones, “Rapid Object Detection Using a Boosted Cascade of Simple Features,” Proceedings of IEEE Computer So Ciety Conference on Computer Vision and Pat Tern Recognition, Kauai, 8-14 December 2001, Vol. 1, p. 511.
|
[2]
|
L. Carminati, J. Benois-Pineau and C. Jennewein, “Knowledge-Based Super Vised Learning Methods in a Classical Problem of Video Object Tracking,” Proceedings of IEEE International Conference on Image Processing, Atlanta, 8-11 October 2006, pp. 2385-2389.
|
[3]
|
H. A. Rowley, S. Baluj and T. Kanade, “Neural Network-Based Face Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No.1, 1998, pp. 23-38. doi:10.1109/34.655647
|
[4]
|
R. Feraud, O. J. Bernier, J. Vialle and M. Collobert, “A Fast and Accurate Face Detector Based on Neural Networks,” IEEE Transactions on Pat Tern Analysis and Machine Intelligence, Vol. 23, No. 1, 2001, pp. 42-53.
doi:10.1109/34.899945
|
[5]
|
C. Papageorgiou, M. Oren and T. Poggio, “A General Famework for Object Detection,” Proceedings of International Conference on Computer Vision, Bombay, 4-7 January 1998, pp. 555-562.
|
[6]
|
C. Liu, “A Bayesian Discriminating Features Method for Face Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 6, 2003, pp. 725-740. doi:10.1109/TPAMI.2003.1201822
|
[7]
|
D. Freedman, “Active Contours for Tracking Distributions,” IEEE Transactions on Image Processing, Vol. 13, No. 4, 2004, pp. 518-526. doi:10.1109/TIP.2003.821445
|
[8]
|
H. T. Nguyen and A. W. M. Smeulders, “Fast Occluded Object Tracking by a Robust Appearance Filter,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 8, 2004, pp. 1099-1104.
|
[9]
|
H.-T. Chen, T.-L. Liu and C.-S. Fuh, “Probabilistic Tracking with Adaptive Feature Selection,” Proceedings of International Conference on Pattern Recognition, Wash- ington DC, Vol. 2, 2004, pp. 736-739.
doi:10.1109/TPAMI.2004.45
|
[10]
|
A. U. Batur and M. H. Hayes, “Adaptive Active Appearance Models,” IEEE Transactions on Image Processing, Vol. 14, No. 11, 2005, pp. 1707-1721.
doi:10.1109/TIP.2005.854473
|
[11]
|
P. Corcoran, M. C. Ionita and I. Bacivarov, “Next Generation Face Tracking Technology Using AAM Techniques,” Proceedings of International Symposium on Signals, Systems and Circuits, Vol. 1, 2007, pp. 1-4.
doi:10.1109/ISSCS.2007.4292639
|
[12]
|
K.-S. Cho, Y.-G. Kim and Y.-B. Lee, “Real-Time Expression Recognition System Using Active Appearance Model and EFM,” Proceedings of International Conference on Computational Intelligence and Security, Guang- zhou, Vol. 1, November 2006, pp. 747-750.
|
[13]
|
P. Yang, Q.-S. Liu and D. N. Metaxas, “Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition,” Proceedings of IEEE Conference on Computer Vision and Image Understanding, Minneapolis, 18-23 June 2007.
|
[14]
|
S Petar, S. Aleksic and A. K. Katsaggelos, “Automatic Facial Expression Recognition Using facial Animation Parameters and Multi-Stream HMMs,” IEEE Transactions on Information Forensics and Security, Vol. 1, 2006, pp. 3-11. doi:10.1109/TIFS.2005.863510
|
[15]
|
L. Ma and K. Khorasani, “Facial Expression Recognition Using Constructive Feed forward Neural Networks,” IEEE Transactions on Systems, Man and Cybernetics, Vol. 34, No. 3, 2004, pp. 1588-1595.
doi:10.1109/TSMCB.2004.825930
|
[16]
|
N. Friedman, D. Geiger and M. Goldszmidt, “Bayesian Network Classifiers,” Machine Learning, Vol. 29, No. 2, 1997, pp. 131-163. doi:10.1023/A:1007465528199
|
[17]
|
N. Sebe, I. Cohen, A. Garg, M. Lew and T. Huang, “Emotion Recognition Using a Cauchy Na?ve Bayes Classifier,” Proceedings of International Conference on Pattern Recognition, Quebec City, Vol. 1, August 2002, pp. 17-20.
|
[18]
|
N. Esau, E. Wetzel, L. Kleinjohann and B. Kleinjohann, “Real-Time Facial Expression Recognition Using a Fuzzy Emotion Model,” IEEE Proceedings of Fuzzy Systems Conference, London, 2007.
|
[19]
|
A. Geetha, V. Ramalingam, S. Palanivel and B. Palaniappan, “Facial Expression Recognition—A Real Time Approach,” International Journal of Expert Systems with Applications, Vol. 36, No. 1, 2009, pp. 303-308.
doi:10.1016/j.eswa.2007.09.002
|
[20]
|
I. Kotsia, N. Nikolaidis and I. Pitas, “Facial Expression Recognition in Videos Using a Novel Multi-Class Support Vector Machines Variant,” Proceedings of International Conference on Acoustics, Speech and Signal Processing, Honolulu, 15-20 April 2007, pp. 585-588.
|
[21]
|
S. Avidan, “Support Vector Tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 8, 2004, pp. 1064-1072.
|
[22]
|
J. C. B. Christopher, “A Tutorial on Support Vector Machines for Pattern Recognition,” Data Mining and Knowledge Discovery, Vol. 2, No. 2, 1998, pp. 121-167.
|
[23]
|
F. Yang and M. Paindavoine, “Implementation of an RBF Neural Network on Embedded Systems: Real-Time Face Tracking and Identity Verification,” IEEE Transactions on Neural Networks, Vol. 14, No. 5, 2003, pp. 1162-1175.
doi:10.1109/TNN.2003.816035
|
[24]
|
S. Haykins, “Neural Networks: A Comprehensive Foundation,” Pearson Publication 2001, Asia.
|
[25]
|
M. T. Musavi, W. Ahmed, K. H. Chan, K. B. Faris and D. M. Hummels, “On the Training of Radial Basis Function Classifiers,” IEEE Transactions on Neural Networks, Vol. 5, No. 4, 1992, pp. 595-603.
|
[26]
|
K. Anderson and P. W. McOwan, “Robust Real-Time Face Tracker for Cluttered Environments,” Computer Vision and Image Understanding, Vol. 95, No. 2, 2004, pp. 184-200. doi:10.1016/j.cviu.2004.01.001
|