A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Trainable System for Object Detection
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Concurrent Self-Organizing Maps for Pattern Classification
ICCI '02 Proceedings of the 1st IEEE International Conference on Cognitive Informatics
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
An Experimental Study on Pedestrian Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle
International Journal of Computer Vision
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pedestrian Detection via Classification on Riemannian Manifolds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Human Detection Using a Novel Boosted Cascading Structure With Meta Stages
IEEE Transactions on Image Processing
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The paper presents an original approach for pedestrian detection using the neural network classifier called Concurrent Self-Organizing Maps (CSOM), previously introduced by first author; it represents a winner-takes-all collection of neural modules. The algorithm has the following stages: (a) feature selection using one of the three candidate techniques Histogram of Oriented Gradients (HOG)/1D Haar transform/2D Haar transform; (b) classification using a CSOM classifier with two concurrent neural modules, where first module is trained with pedestrian images and the second one is trained with non-pedestrian images. We present the experimental results obtained by computer simulation of our model. For training and testing the neural classifier, we have used INRIA Person Dataset. One obtains the best Total Success Rate (TSR) of 99.7%.