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Deep neural networks for mobile person recognition with audio-visual signals

Alam, M.R., Bennamoun, M., Togneri, R. and Sohel, F. (2017) Deep neural networks for mobile person recognition with audio-visual signals. In: Guo, G. and Wechsler, H., (eds.) Mobile Biometrics. IET Digital Library, pp. 97-129.

Link to Published Version: https://doi.org/10.1049/PBSE003E_ch4
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Abstract

This chapter starts with a general and brief introduction of biometrics and audiovisual person recognition using mobile phone data. It begins with a discussion of what constitutes a biometric recognition system, and it then details the steps followed when audio-visual signals are used as inputs. This is followed by a review of the existing speaker and face recognition systems which have been evaluated on a mobile biometric database. We then discuss the key motivations of using deep neural network (DNN) for person recognition. We finally introduce a Deep Boltzmann Machine (DBM)- DNN, in short DBM-DNN, based framework for person recognition. An overview of the sections and sub-sections of this chapter is shown in Figure 4.1.

Item Type: Book Chapter
Murdoch Affiliation(s): College of Arts, Business, Law and Social Sciences
Publisher: IET Digital Library
URI: http://researchrepository.murdoch.edu.au/id/eprint/62391
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