AdaBoost face detection on the gpu using Haar-like features

Authors:
M. Martínez-Zarzuela;F. J. Díaz-Pernas;M. Antón-Rodríguez;F. Perozo-Rondón;D. González-Ortega
Affiliations:
Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain
Venue:
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
Year:
2011

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Abstract

Face detection is a time consuming task in computer vision applications. In this article, an approach for AdaBoost face detection using Haar-like features on the GPU is proposed. The GPU adapted version of the algorithm manages to speed-up the detection process when compared with the detection performance of the CPU using a well-known computer vision library. An overall speed-up of × 3.3 is obtained on the GPU for video resolutions of 640×480 px when compared with the CPU implementation. Moreover, since the CPU is idle during face detection, it can be used simultaneously for other computer vision tasks.