TY - GEN
T1 - Classifying children with 3D depth cameras for enabling children's safety applications
AU - Basaran, Can
AU - Yoon, Hee Jung
AU - Ra, Ho Kyung
AU - Son, Sang Hyuk
AU - Park, Taejoon
AU - Ko, Jeong Gil
N1 - Publisher Copyright:
Copyright © 2014 by the Association for Computing Machinery, Inc. (ACM).
Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2014
Y1 - 2014
N2 - In this work, we present ChildSafe, a classification sys- Tem which exploits human skeletal features collected us- ing a 3D depth camera to classify visual characteristics between children and adults. ChildSafe analyzes the histograms of training samples and implements a bin- boundary-based classifier. We train and evaluate Child- Safe using a large dataset of visual samples collected from 150 elementary school children and 43 adults, rang- ing in the ages of 7 and 50. Our results suggest that ChildSafe successfully detects children with a proper classification rate of up to 97%, a false negative rate of as low as 1.82%, and a low false positive rate of 1.46%. We envision this work as an effective sub-system for de- signing various child protection applications.
AB - In this work, we present ChildSafe, a classification sys- Tem which exploits human skeletal features collected us- ing a 3D depth camera to classify visual characteristics between children and adults. ChildSafe analyzes the histograms of training samples and implements a bin- boundary-based classifier. We train and evaluate Child- Safe using a large dataset of visual samples collected from 150 elementary school children and 43 adults, rang- ing in the ages of 7 and 50. Our results suggest that ChildSafe successfully detects children with a proper classification rate of up to 97%, a false negative rate of as low as 1.82%, and a low false positive rate of 1.46%. We envision this work as an effective sub-system for de- signing various child protection applications.
UR - http://www.scopus.com/inward/record.url?scp=84908593692&partnerID=8YFLogxK
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U2 - 10.1145/2632048.2636074
DO - 10.1145/2632048.2636074
M3 - Conference contribution
AN - SCOPUS:84908593692
T3 - UbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
SP - 343
EP - 347
BT - UbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PB - Association for Computing Machinery, Inc
T2 - 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014
Y2 - 13 September 2014 through 17 September 2014
ER -