FPGA implementation of a neural network for a real-time hand tracking system

被引:30
作者
Krips, M [1 ]
Lammert, T [1 ]
Kummert, A [1 ]
机构
[1] Univ Wuppertal, Dept Elect & Informat Engn, D-42119 Wuppertal, Germany
来源
FIRST IEEE INTERNATION WORKSHOP ON ELECTRONIC DESIGN, TEST AND APPLICATIONS, PROCEEDINGS | 2002年
关键词
D O I
10.1109/DELTA.2002.994637
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The advantage of parallel computing of artificial neural networks can be combined with the potentials of VLSI circuits in. order to design a real time detection and tracking system applied to video images. Based on these facts, a real-time localization and tracking algorithm has been developed for detecting human hands in video images. Due to the real time aspect, a single-pixel-based classification is aspired, so that a continuous data stream can be processed. Consequently,, no storage of full images or parts of them is necessary. The classification, whether a pixel belongs to a hand or to the background, is done by analyzing the RGB-values of a single pixel by means of an artificial neural network. To obtain the full processing speed of this neural network a hardware solution is realized in a Field Programmable Gate Array (FPGA).
引用
收藏
页码:313 / 317
页数:5
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