Context-Assisted Fast Face Detection

Abstract:

In this paper, we propose a novel algorithm for fast face detection in camera video. By extending the task of face detection from solely relying on visual data of camera sensor to cooperatively analyzing synchronized information of multiple sensors, we greatly reduce the time cost of face detection. Specifically, when subjects wearing motion sensors move around in the field of view (FOV) of a camera, motion status estimated from the wearable sensors helps to decide when is the good time to start face detection, and thus save large amount of work previously spent on filtering out faceless frames. To test the technical feasibility and efficiency of the proposed method, we conducted extensive experiments and compared it with state-of-the-art algorithms. Results indicate that the proposed algorithm achieves significant improvements in terms of time cost.

• Periodical: Applied Mechanics and Materials (Volumes 571-572)
• Pages: 863-866
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.571-572.863
• Online since: June 2014
• Authors: Ding Bo Duan*, Jian Ma
• Keywords: Context-Assisted, Face Detection, Smart Phone

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