P-FAD: Real-Time Face Detection Scheme on Embedded Smart Cameras

Abstract

Face detection on general embedded devices is fundamentally different from the conventional approach on personal computer or consumer digital camera due to the limited computation and power capacity. The resource-limited characteristic gives rise to new challenges for implementing a real-time video surveillance system with smart cameras. In this work, we present the design and implementation of Pyramid-like FAce Detection (P-FAD), a real-time face detection system constructed on general embedded devices. Motivated by the observation that the computation overhead increases proportionally to its pixel manipulation, P-FAD proposes a hierarchical approach to shift the complex computation to the promising regions. More specifically, P-FAD present a three-stage coarse, shift, and refine procedure, to construct a pyramid-like detection framework for reducing the computation overhead significantly. This framework also strikes a balance between the detection speed and accuracy. We have implemented P-FAD on notebook, Android phone and our embedded smart camera platform. An extensive system evaluation in terms of detailed experimental and simulation results is provided. Our empirical evaluation shows that P-FAD outperforms V-J detector calibrated color detector (VJ-CD) and color detector followed by a V-J detector (CD-VJ), the state of the art real-time face detection techniques by 4.7 -8.6 on notebook and by up to 8.2 on smart phone in terms of thembedded smart camera platfoe detection speed.