A 700fps optimized coarse to fine shape searching based hardware accelerator for face alignment
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.
2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC)