臺灣博碩士論文加值系統

Face detection is the process of locating the position where faces are present in an image.Currently, software-based face detection is hard to support real-time video streams in an embedded processor. By hardware and software co-analysis, we design a hardware imple-mentation of face detection which satisfies embedded constraints. The experimental results of our hardware design show that the video streams provided by RGB camera can be exe-cuted in real-time and the cost of hardware resource is also relatively low. We also analyze our detection rate and false positive number under different threshold settings and lighting conditions.

Abstract i
1 Introduction 1
2 Related Work 5
3 Face Detection Algorithm 7
3.1 Skin-Color Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3.2 Edge Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.3 Feature Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4 Hardware Implementation of Face Detection 14
4.1 Hardware Design Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.1.1 Virtex-4 ML402 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.1.2 Video I/O Daughter Card . . . . . . . . . . . . . . . . . . . . . . . . 15
4.1.3 LVDS RGB Camera . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4.1.4 Hardware Platform Diagram . . . . . . . . . . . . . . . . . . . . . . . 16
4.2 Hardware and Software Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.3 Hardware Implementation of Skin-Color Filter . . . . . . . . . . . . . . . . . 18
4.4 Hardware Implementation of Edge Detection . . . . . . . . . . . . . . . . . . 18
4.5 Hardware Implementation of Feature Detection . . . . . . . . . . . . . . . . 19
4.6 Xilinx Design Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.7 Pipelined Flow of Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
5 Experimental Results 23
6 Conclusion 27

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