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

Author

Hefenbrock, Daniel ; Oberg, Jason ; Thanh, Nhat Tan Nguyen ; Kastner, Ryan ; Baden, Scott B.

Author_Institution

Dept. of Comput. Sci. & Eng., Univ. of California, San Diego, La Jolla, CA, USA

fYear

2010

fDate

2-4 May 2010

Firstpage

11

Lastpage

18

Abstract

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.

Keywords

computer graphic equipment; coprocessors; face recognition; field programmable gate arrays; object detection; FPGA-level; GPU design; Viola-Jones face detection; biometrics; human computer interaction; multiGPU implementation; video surveillance; Acceleration; Algorithm design and analysis; Application software; Application specific integrated circuits; Costs; Face detection; Field programmable gate arrays; Hardware; Object detection; Timing; Acceleration; Face Detection; Field Programmable Gate Array; Graphical Processing Unit;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Charlotte, NC

Print_ISBN

978-0-7695-4056-6

Electronic_ISBN

978-1-4244-7143-0

Type

conf

DOI

10.1109/FCCM.2010.12

Filename

5474075