Real Time GPU-Based Fuzzy ART Skin Recognition

Authors:
Mario Martínez-Zarzuela;Francisco Javier Díaz Pernas;David González Ortega;José Fernando Díez Higuera;Míriam Antón Rodríguez
Affiliations:
Higher School of Telecommunications Engineering, University of Valladolid, Spain);Higher School of Telecommunications Engineering, University of Valladolid, Spain);Higher School of Telecommunications Engineering, University of Valladolid, Spain);Higher School of Telecommunications Engineering, University of Valladolid, Spain);Higher School of Telecommunications Engineering, University of Valladolid, Spain)
Venue:
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Year:
2007

Citing 7
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Abstract

Graphics Processing Units (GPUs) have evolved into powerful programmable processors, becoming increasingly used in many research fields such as computer vision. For non-intrusive human body parts detection and tracking, skin filtering is a powerful tool. In this paper we propose the use of a GPU-designed implementation of a Fuzzy ART Neural Network for robust real-time skin recognition. Both learning and testing processes are done on the GPU using chrominance components in TSL color space. Within the GPU, classification of several pixels can be made simultaneously, allowing skin recognition at high frame rates. System performance depends both on video resolution and number of neural network committed categories. Our application can process 296 fps or 79 fps at video resolutions of 320x240 and 640x480 pixels respectively.