In this work, a fast shape searching face alignment (F-SSFA) algorithm based accelerator is proposed to achieve real-time processing. Firstly, a learning based low-dimensional SURF feature is introduced to reduce the computation cost in the cascaded regression. Then the Euclidean distance and shape affine transformation are utilized to accelerate the shape searching procedure. F-SSFA therefore greatly reduces the computational complexity while keeping the same accuracy. Also, a fixed-point F-SSFA based VLSI architecture is designed with approximately 80% decrease in the data transmission traffic. The throughput of this accelerator achieves 700 fps, which is especially suitable for high-speed facial-related applications.
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