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Robust and rapid object detection is one of the great challenges in the field of computer vision. This paper proposes a hardware architecture suitable for object detection by Viola and Jones [9] based on an AdaBoost learning algorithm with Haar-like features as weak classifiers. Our architecture realizes rapid and robust detection with two major features:(More)
In pedestrian detection, as sophisticated feature descriptors are used for improving detection accuracy, its processing speed becomes a critical issue. In this paper, we propose a novel speed-up scheme based on multiple-instance pruning (MIP), one of the soft cascade methods, to enhance the processing speed of support vector machine (SVM) classifiers. Our(More)