Hardware/software co-design for a gender recognition embedded system

Authors

Andrew Tzer - Yeu Chen, University of AucklandFollow
Morteza Biglari-Abhari, University of Auckland
Kevin I-Kai Wang, University of Auckland
Abdesselam Bouzerdoum, University of WollongongFollow
Fok Hing Chi Tivive, University of WollongongFollow

RIS ID

107135

Publication Details

A. Tzer-Yeu. Chen, M. Biglari-Abhari, K. I-Kai. Wang, A. Bouzerdoum & F. Tivive , "Hardware/software co-design for a gender recognition embedded system," Lecture notes in computer science, vol. 9799, pp. 541-552, 2016.

Abstract

Gender recognition has applications in human-computer interaction, biometric authentication, and targeted marketing. This paper presents an implementation of an algorithm for binary male/female gender recognition from face images based on a shunting inhibitory convolutional neural network, which has a reported accuracy on the FERET database of 97.2 %. The proposed hardware/software co-design approach using an ARM processor and FPGA can be used as an embedded system for a targeted marketing application to allow real-time processing. A threefold speedup is achieved in the presented approach compared to a software implementation on the ARM processor alone.