Audio-visual recognition system insusceptible to illumination variation over internet protocol

In this paper, we present an audio-visual recognition system which is insusceptible to illumi nation variation over internet protocol. First, the multiband feature fusion method is proposed for face recognition unde r varying illumination. The wavelet packet transform decompose s an image into various frequency subbands. We show how to select a set of subbands that are invariant to illumination variations by using statistical method and modified Euclidean base d method. More specifically, there exist a set of wavelet sub bands that carry facial features which provide an effective representation for face recognition under wide range of lighting conditions. Histogram equalization is then applied on these sub bands to enhance the contrast of the features. The recognitio n performance of the proposed method is validated on some standard data sets and high recognition accuracy is achieved. Then the audio-visual recognition system over intern et protocol is developed. The compression and packet loss effect s of sending the audio and video data over internet protocol on recognition performance are investigated.

[1]  J.N. Gowdy,et al.  CUAVE: A new audio-visual database for multimodal human-computer interface research , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[2]  Wei Ding,et al.  Rate control of MPEG video coding and recording by rate-quantization modeling , 1996, IEEE Trans. Circuits Syst. Video Technol..

[3]  Amnon Shashua,et al.  The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Yuan Yan Tang,et al.  Multiscale facial structure representation for face recognition under varying illumination , 2009, Pattern Recognit..

[5]  Pong C. Yuen,et al.  Human face recognition using PCA on wavelet subband , 2000, J. Electronic Imaging.

[6]  Marian Stewart Bartlett,et al.  Face recognition by independent component analysis , 2002, IEEE Trans. Neural Networks.

[7]  Georgios Tziritas,et al.  Wavelet packet analysis for face recognition , 2000, Image Vis. Comput..

[8]  David J. Kriegman,et al.  From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Bülent Sankur,et al.  ARTICLE IN PRESS Image and Vision Computing xx (2005) 1–9 www.elsevier.com/locate/imavis , 2004 .

[10]  Siwei Luo,et al.  Illumination ratio image: synthesizing and recognition with varying illuminations , 2003, Pattern Recognit. Lett..

[11]  David J. Kriegman,et al.  What Is the Set of Images of an Object Under All Possible Illumination Conditions? , 1998, International Journal of Computer Vision.

[12]  Farzin Deravi,et al.  A review of speech-based bimodal recognition , 2002, IEEE Trans. Multim..

[13]  Rabab Kreidieh Ward,et al.  Wavelet-based illumination normalization for face recognition , 2005, IEEE International Conference on Image Processing 2005.

[14]  Sanjit K. Mitra,et al.  Rate-distortion optimized mode selection for very low bit rate video coding and the emerging H.263 standard , 1996, IEEE Trans. Circuits Syst. Video Technol..

[15]  Juyang Weng,et al.  Using Discriminant Eigenfeatures for Image Retrieval , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  John H. Smith.  Preparation of Papers for the IAENG International Journal of Computer Science , 2009 .

[17]  Kah Phooi Seng,et al.  Audio-Visual Recognition System with Intra-Modal Fusion , 2007, 2007 International Conference on Computational Intelligence and Security (CIS 2007).

[18]  Aleix M. Martinez,et al.  The AR face database , 1998 .

[19]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[20]  David J. Kriegman,et al.  Acquiring linear subspaces for face recognition under variable lighting , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[22]  Lei Zhang,et al.  Face recognition under variable lighting using harmonic image exemplars , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[23]  Sukhendu Das,et al.  Selection of Wavelet Subbands Using Genetic Algorithm for Face Recognition , 2006, ICVGIP.

[24]  Chad Zhu.  RTP Payload Format for H.263 Video Streams , 1997, RFC.

[25]  Jon M. Peha,et al.  Streaming video over the Internet: approaches and directions , 2001, IEEE Trans. Circuits Syst. Video Technol..

[26]  Dorin Comaniciu,et al.  Total variation models for variable lighting face recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  C. Burrus,et al.  Introduction to Wavelets and Wavelet Transforms: A Primer , 1997 .

[28]  Ralph Gross,et al.  Person identification using automatic integration of speech, lip, and face experts , 2003, WBMA '03.

[29]  Kah Phooi Seng,et al.  Audio-Visual Recognition System with Intra-Modal Fusion , 2007 .

[30]  Meng Joo Er,et al.  Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[31]  Alex Pentland,et al.  Flexible Images: Matching and Recognition Using Learned Deformations , 1997, Comput. Vis. Image Underst..

[32]  Haitao Wang,et al.  Face recognition under varying lighting conditions using self quotient image , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[33]  Jr. J.P. Campbell,et al.  Speaker recognition: a tutorial , 1997, Proc. IEEE.

[34]  Shimon Ullman,et al.  Face Recognition: The Problem of Compensating for Changes in Illumination Direction , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[35]  Wen Gao,et al.  Illumination normalization for robust face recognition against varying lighting conditions , 2003, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443).