Title: Deep learning on a Raspberry Pi for real time face recognition
Authors : Dürr, Oliver
Pauchard, Yves
Browarnik, Diego Hernan
Axthelm, Rebekka
Loeser, Martin
Proceedings: EG 2015 - Posters
Pages : 11
Pages to: 12
Conference details: EG 2015, Eurographics Conference, Zurich, 4-8 May 2015
Publisher / Ed. Institution : The Eurographics Association
Issue Date: 2015
License (according to publishing contract) : Licence according to publishing contract
Type of review: Not specified
Language : English
Subjects : Face recognition; Raspberry Pi; Deep learning
Subject (DDC) : 004: Computer science
Abstract: In this paper we describe a fast and accurate pipeline for real-time face recognition that is based on a convolutional neural network (CNN) and requires only moderate computational resources. After training the CNN on a desktop PC we employed a Raspberry Pi, model B, for the classification procedure. Here, we reached a performance of approximately 2 frames per second and more than 97% recognition accuracy. The proposed approach outperforms all of OpenCV's algorithms with respect to both accuracy and speed and shows the applicability of recent deep learning techniques to hardware with limited computational performance.
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Institute of Data Analysis and Process Design (IDP)
Institute for Signal Processing and Wireless Communications (ISC)
Publication type: Conference Poster
DOI : 10.2312/egp.20151036
URI: https://digitalcollection.zhaw.ch/handle/11475/13891
Appears in Collections:Publikationen School of Engineering

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