A specialized processor suitable for AdaBoost-based detection with haar-like features

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2007, Pages

  Hiromoto, Masayuki ^a   Nakahara, Kentaro ^a   Sugano, Hiroki ^a   Nakamura, Yukihiro ^b   Miyamoto, Ryusuke ^c  

^a KYOTO UNIVERSITY   (Japan)

^b RITSUMEIKAN UNIVERSITY   (Japan)

^c NARA INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ADA (PROGRAMMING LANGUAGE); COMPUTER HARDWARE; COMPUTER VISION; PROGRAM PROCESSORS; REAL TIME SYSTEMS; ROBUSTNESS (CONTROL SYSTEMS);

ADABOOST; HARDWARE ARCHITECTURE; IMAGE SCALING; OBJECT DETECTION;

OBJECT RECOGNITION;

EID: 34948827437     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2007.383415     Document Type: Conference Paper

References (13)

1. OpenCV Library. http://sourceforge.net/projects/opencvlibrary/.
2. R. Lienhart and J. Maydt. An extended, set of Haar-like features for rapid object detection. In Proc. IEEE Int'l Conf. Image Processing, volume 1, 2002.
3. W. MacLean. An Evaluation of the Suitability of FPGAs for Embedded Vision Systems. In Proc. IEEE Conf. Computer Vision and Pattern Recognition Workshop, pages 131-138, 2005.
4. R. Miyamoto, H. Sugano, H. Saito, H. Tsutsui, H. Ochi, K. Hatanaka, and. Y. Nakamura. Pedestrian recognition in far-infrared images by combining boosting-based detection and skeleton-based stochastic tracking. In Proc. first IEEE Pacific-Rim Symp. Image and Video Technology, pages 483-494, December 2006.
5. V. Nair, P. Laprise, and J. Clark. An FPGA-Based People Detection System. EURASIP J. Applied Signal Processing, 2005(7):1047-1061, 2005.
6. H. Rowley, S. Baluja, and T. Kanade. Neural network-based face detection. IEEE Trans. Pattern Analysis and Machine Intelligence, 20(1):23-38, 1998.
7. M. Sen, I. Corretjer, F. Haim, S. Saha, J. Schlessman, S. Bhattacharyya, and W.Wolf. Computer Vision on FPGAs: Design Methodology and its Application to Gesture Recognition. In Proc. IEEE Conf. Computer Vision and Pattern Recognition Workshop, pages 133-141, 2005.
8. T. Theocharides, N. Vijaykrishnan, and M. J. Irwin. A parallel architecture for hardware face detection. In Proc. IEEE Computer Society Ann. Symp. Emerging VLSI Technologies and Architectures, pages 452-453, 2006.
9. P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, volume 1, pages 511-518, 2001.
10. P. Viola and M. Jones. Robust real-time object detection. Int'l J. Computer Vision, 57(2):137-154, 2002.
11. P. Viola, M. Jones, and D. Snow. Detecting Pedestrians Using Patterns of Motion and Appearance. Int'l J. Computer Vision, 63(2):153-161, 2005.
12. Y. Wei, X. Bing, and C. Chareonsak. FPGA implementation of AdaBoost algorithm for detection of face biometrics. In Proc. IEEE Int'l Workshop Biomedical Circuits and Systems, page S1, 2004.
13. M. Yang, Y. Wu, J. Crenshaw, B. Augustine, and R. Mareachen. Face detection for automatic exposure control in handheld camera. In Proc. IEEE Int'l Conf. Computer Vision Systems, page 17, 2006.