Abstract
This live demonstration shows an FPGA-based real-time hand sign recognition system. The system consists of a feature vector extraction and a vector classifier. The SOM-Hebb classifier network is used for the classification network, which is made of a self-organizing map and a feed-forward neural network. Training of the SOM-Hebb classifier is carried out by an off-chip computer. In this demonstration, the hand sign recognition camera is tuned by a newly developed training algorithm for the off-chip learning.
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