AdaBoost Face Detection on the GPU Using Haar-Like Features
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 640x480 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.
KeywordsFace Detection Adaboost Haar-like features GPU CUDA OpenGL
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- 1.CellCV: Opencv on the cell. adaboost face detection using haar-like features optimization for the cell. code downloading and performance comparisons (2009), http://cell.fixstars.com/opencv/index.php/Facedetect (last Visit February 2009)
- 2.Crow, F.C.: Summed-area tables for texture mapping. In: SIGGRAPH 1984: Proceedings of the 11th Annual Conference on Computer Graphics and Interactive Techniques, pp. 207–212. ACM Press, New York (1984)Google Scholar
- 3.Elkan, C.: Boosting and naive bayesian learning. Tech. rep. (1997)Google Scholar
- 6.Rowley, H.A., Baluja, S., Kanade, T.: Neural network-based face detection. IEEE Transactions on PAMI (1998)Google Scholar
- 8.Harris, M.: Parallel prefix sum (scan) with cuda. In: Nguyen, H. (ed.) GPU Gems 3, ch. 39, pp. 851–876. Addison Wesley Professional, Reading (2007)Google Scholar
- 9.Hiromoto, M., Nakahara, K., Sugano, H., Nakamura, Y., Miyamoto, R.: A specialized processor suitable for adaboost-based detection with haar-like features. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. 1–8 (June 2007)Google Scholar
- 11.OpenCV: Open source computer vision library (2009), http://sourceforge.net/projects/opencvlibrary (last visit February 2009)
- 12.Rabiner, L.R.: A tutorial on hidden markov models and selected applications in speech recognition, pp. 267–296 (1990)Google Scholar
- 13.Romdhani, S., Torr, P., Scholkopf, B., Blake, A.: Computationally efficient face detection. In: IEEE International Conference on Computer Vision, vol. 2, p. 695 (2001)Google Scholar
- 14.Shi, Y., Zhao, F., Zhang, Z.: Hardware implementation of adaboost algorithm and verification. In: 22nd International Conference on Advanced Information Networking and Applications - Workshops, AINAW 2008, pp. 343–346 (March 2008)Google Scholar
- 15.Vaillant, R., Monrocq, C., Le Cun, Y.: Original approach for the localization of objects in images. In: IEEE Proceedings of Vision, Image and Signal Processing, vol. 141(4), pp. 245–250 (August 1994)Google Scholar