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Real Time GPU-Based Fuzzy ART Skin Recognition

机译:基于GPU的实时模糊ART皮肤识别

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摘要

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 640×480 pixels respectively.
机译:图形处理单元(GPU)已发展成为功能强大的可编程处理器,并越来越多地用于许多研究领域,例如计算机视觉。对于非侵入式人体部位检测和跟踪,皮肤过滤是一种强大的工具。在本文中,我们建议使用GPU设计的Fuzzy ART神经网络实现稳定的实时皮肤识别。学习和测试过程都是使用TSL颜色空间中的色度组件在GPU上完成的。在GPU内,可以同时进行几个像素的分类,从而以高帧频识别皮肤。系统性能取决于视频分辨率和神经网络承诺类别的数量。我们的应用程序可以分别以320x240和640×480像素的视频分辨率处理296 fps或79 fps。

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