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This paper investigates head pose estimation problem which is considered as front-end preprocessing for improving multi-view human face recognition. We propose a computational model for perceiving head pose based on neurophysiologi-cal plausible invariance representation. In order to obtain the invariance representa tion bases or facial multi-view bases, a learning algorithm is derived for training the linear representation model. Then the facial multi-view bases are used to construct the computational model for head pose perception. The measure for head pose per ception is introduced that the final-layered winner neuron gives the resulting head pose, if its connected pre-layer has the most firing neurons. Computer simulation results and comparisons show that the proposed model achieves satisfactory accuracy for head pose estimation of facial multi-view images in the CAS-PEAL face database.
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References
H.B. Barlow. Redundancy reduction revisited. Network-Comp Neural, 12:241-253, 2001.
A. Cichocki, and L. Zhang. Two-stage blind deconvolution using state-space models. In: Usui S, Omori, T (Eds.) The fifth international conference on neural information processing (ICONIP), Kitakyushu, Japan, pp 729-732, 1998.
W. Gao, B. Cao, et al. The CAS-PEAL large-scale Chinese face database and evaluation protocols. Technical Report No. JDL-TR-04-FR-001, Joint Research & Development Laboratory, 2004.
D. Hubel, and T. Wiesel. Receptive fields and functional architecture of monkey striate cortex. J Physiol, 195:215-243, 1968.
A. Hyvarinen, and P.O. Hoyer. Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces. Neural Comput, 12(7):1705-1720, 2000.
S. Li, X. Lv, X. et al. Learning multi-view face subspaces and facial pose estimation using independent component analysis. IEEE T Image Process, 14(6):705-712, 2005.
B. Ma, W. Zhang, et al. Robust head pose estimation using LGBP. In: Tang YY, Wang SP, Lorette G, Yeung DS, Yan H (Eds.) Proceeding of international conference on pattern recognition, 2:512-515, 2006.
S. McKenna, and S. Gong. Real time face pose estimation. Real-Time Imaging, 4(5):333-347, 1998.
B.A. Olshausen, and D.J. Field. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381:607-609, 1996.
W. Peng, and J. Qiang. Multi-view and eye detection using discriminant features. Comput Vis Image Und, 105:99-111, 2007.
L.K. Saul, and S.T. Roweis. Think globally, fit locally: unsupervised learning of low dimensional manifolds. J Mach Learn Res, 4:119-155, 2003.
L. Zhang, A. Cichocki, and S. Amari. Self-adaptive blind source separation based on activation function adaptation. IEEE T Neural Network, 15(2):233-244, 2004.
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Authors and Affiliations
Lab for Perception Computing, Shanghai Jiao Tong University, China
Wenlu Yang & Liqing Zhang
Department of Electronic Engineering, Shanghai Maritime University, China
Wenlu Yang
- Wenlu Yang
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- Liqing Zhang
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Editors and Affiliations
Technische Universität Berlin, Berlin, Germany
Bernd Mahr
Shanghai Jiao Tong University, Shanghai, China
Sheng Huanye
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Yang, W., Zhang, L. (2008). Head Pose Perception Based on Invariance Representation. In: Mahr, B., Huanye, S. (eds) Autonomous Systems – Self-Organization, Management, and Control. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8889-6_1
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