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Accelerating Viola-Jones Face Detection to FPGA-Level Using GPUs

Daniel Hefenbrock, Jason Oberg, Nhat Tan Nguyen Thanh, Ryan Kastner, Scott B. Baden
Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California, USA
18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2010

@inproceedings{hefenbrock2010accelerating,

   title={Accelerating viola-jones face detection to fpga-level using gpus},

   author={Hefenbrock, D. and Oberg, J. and Thanh, N. and Kastner, R. and Baden, S.B.},

   booktitle={Field-Programmable Custom Computing Machines (FCCM), 2010 18th IEEE Annual International Symposium on},

   pages={11–18},

   year={2010},

   organization={IEEE}

}

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Face detection is an important aspect for biometrics, video surveillance and human computer interaction. We present a multi-GPU implementation of the Viola-Jones face detection algorithm that meets the performance of the fastest known FPGA implementation. The GPU design offers far lower development costs, but the FPGA implementation consumes less power. We discuss the performance programming required to realize our design, and describe future research directions.
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