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The authors describe a High-Level Synthesis implementation of a parallel architecture for face detection. The chosen face detection method is the well-known Convolutional Face Finder (CFF) algorithm, which consists of a pipeline of convolution operations. They rely on dataflow modelling of the algorithm and they use a high-level synthesis tool in order to specify the local dataflows of their Processing Element (PE), by describing in C language inter-PE communication, fine scheduling of the successive convolutions, and memory distribution and bandwidth. Using this approach, they explore several implementation alternatives in order to find a compromise between processing speed and area of the PE.
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