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Conference Paper HW/SW co-design of Face Detection & Recognition on Virtual Platform
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Authors
Mi-Young Lee, Young-Seok Baek, Seong-Min Kim, Hyuk Kim, Bon-Tae Koo, Joo-Hyun Lee
Issue Date
2016-10
Citation
International Conference on Consumer Electronics (ICCE) 2016 : Asia, pp.307-308
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICCE-Asia.2016.7804730
Abstract
In this paper, we present a FPGA implementation of face detection hardware (HW) and also address face recognition software (SW) on virtual platform. We apply very deeply-cascaded classifier which is composed of heterogeneous feature-classifiers to capture various characteristics of images. We use 2 step classifiers, the first searches for the coarse features and the second for the fine features. Both of the features are composed of HAAR like feature classifiers and Gabor classifiers while the 1st coarse classifier uses 700 classifiers and the 2nd uses 1350 classifiers. For the very-deeply cascaded face detector, we developed dedicated HW engine to process a feature per a cycle. The face detection is implemented in a Xilinx Virtex-7 device. For face recognition SW co-design, we also developed a virtual platform (VP). We co-verified face detection engine and face recognition SW running on a conventional operating system (OS) using the VP. Face detector operates over 30 frame/s at 50 MHz frequency for real-Time applications up-To 640x480 size image.
KSP Keywords
Cascaded classifier, FPGA Implementation, HW/SW Co-Design, Heterogeneous Feature, Real-Time applications, Virtual platform, Xilinx virtex, face Recognition, face detection, haar-like features, operating system