Abstract
In this paper, we present a facial expression recognition (FER) system implemented on a SoC FPGA device. Our system can operate independently and automatically classify 7 different types of basic emotions. We designed a processing engine on FPGA that is able to calculate convolutional layers of convolutional neural networks and designed a CNN optimal with a designed hardware for the task of emotions recognition and achieving 66% of accuracy in FER2013 dataset. The whole hardware system is designed on SoC FPGA which can process up to 15 image frames per second at an operating frequency of 130 MHz.
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