FastWavelet-Based Visual Classification

We investigate a biologically motivated approach to fast visual classification, directly inspired by the recent work [13]. Specifically, trading-off biological accuracy for computational efficiency, we explore using standard wavelet transforms and patch transforms to parallel the tuning of visual cortex V1 and V4 cells, alternated with max operations to achieve scale and translation invariance. A feature selection procedure is applied during learning to accelerate recognition. We introduce a simple attention-like feedback mechanism, significantly improving recognition and robustness in multiple-object scenes. In experiments, the proposed algorithm achieves or exceeds state-of-the-art performance in object recognition, but also in new applications such as texture classification, satellite image classification, and language identification. Preliminary results on sound classification are shown as well.

[1]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[2]  Jean-Jacques E. Slotine,et al.  On partial contraction analysis for coupled nonlinear oscillators , 2004, Biological Cybernetics.

[3]  Shijian Lu,et al.  Script and Language Identification in Noisy and Degraded Document Images , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  DeLiang Wang,et al.  A dynamically coupled neural oscillator network for image segmentation , 2002, Neural Networks.

[5]  Cordelia Schmid,et al.  A sparse texture representation using local affine regions , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[7]  Pietro Perona,et al.  Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[8]  S. Yoshizawa,et al.  An Active Pulse Transmission Line Simulating Nerve Axon , 1962, Proceedings of the IRE.

[9]  Bin Luo,et al.  Extrapolation of Wavelet Features for the Indexing of Satellite Images with Different Resolutions , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[10]  David G. Lowe,et al.  Multiclass Object Recognition with Sparse, Localized Features , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[11]  Jean-Jacques E. Slotine,et al.  Global Convergence Rates of Nonlinear Diffusion for Time-Varying Images , 1999, Scale-Space.

[12]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[13]  Trygve Randen,et al.  Filtering for Texture Classification: A Comparative Study , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  R. FitzHugh.  Impulses and Physiological States in Theoretical Models of Nerve Membrane. , 1961, Biophysical journal.

[15]  Pietro Perona,et al.  Unsupervised Learning of Models for Recognition , 2000, ECCV.

[16]  Rajesh P. N. Rao,et al.  Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. , 1999 .

[17]  M. Sur,et al.  Visual behaviour mediated by retinal projections directed to the auditory pathway , 2000, Nature.

[18]  Thomas Serre,et al.  Modeling feature sharing between object detection and top-down attention , 2005 .

[19]  Hang Joon Kim,et al.  Support Vector Machines for Texture Classification , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Bin Luo,et al.  Indexing of Satellite Images With Different Resolutions by Wavelet Features , 2008, IEEE Transactions on Image Processing.

[21]  V. Mountcastle,et al.  An organizing principle for cerebral function : the unit module and the distributed system , 1978 .

[22]  Thomas Serre,et al.  Robust Object Recognition with Cortex-Like Mechanisms , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  DeLiang Wang,et al.  Texture classification using spectral histograms , 2003, IEEE Trans. Image Process..

[24]  Jean-Jacques E. Slotine,et al.  Stable concurrent synchronization in dynamic system networks , 2005, Neural Networks.

[25]  Jean-Michel Morel,et al.  Report on Fully Affine Invariant Image Comparison , 2008 .

[26]  J. Hawkins,et al.  On Intelligence , 2004 .