Oriented gradients for human action recognition
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
International Journal of Speech Technology
Context and profile based cascade classifier for efficient people detection and safety care system
Multimedia Tools and Applications
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In this paper, a novel real-time human detection system based on Viola's face detection framework and Histograms of Oriented Gradients (HOG) features is presented. Each bin of the histogram is treated as a feature and used as the basic building element of the cascade classifier. The system keeps both the discriminative power of HOG features for human detection and the real-time property of Viola's face detection framework. Experiments on DaimlerChrysler pedestrian benchmark data set and INRIA human database demonstrate that this framework is more powerful than Viola's object detection framework on human detection.