GS4-2 Human gait recognition based on Caffe deep learning framework

Title:	GS4-2 Human gait recognition based on Caffe deep learning framework
Publication:	ICAROB2018
Volume:	23
Pages:	109-111
ISSN:	2188-7829
DOI:	10.5954/ICAROB.2018.GS4-2
Author(s):	Jiwu Wang, Feng Chen
Publication Date:	February 2, 2018
Keywords:	deep learning, faster rcnn, gait recognition, contour recognition, feature extraction
Abstract:	Human gait recognition as an emerging biometrics technology has important theoretical significance and practical value. At present, the research on human gait recognition is still in the stage of theoretical exploration. With the development of deep learning theory and technology, this paper will achieve human gait recognition of specific targets based on Caffe deep learning framework through the faster-rcnn algorithm. The main contents of the paper include the samples processing, model training and result testing.
PDF File:	https://alife-robotics.co.jp/members2018/icarob/data/html/data/GS_pdf/GS4/GS4-2.pdf
Copyright:	© The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/