loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: R. Škoviera 1 ; K. Valentín 1 ; S. Štolc 2 and I. Bajla 3

Affiliations: 1 Slovak Academy of Sciences and Comenius University, Slovak Republic ; 2 AIT Austrian Institute of Technology GmbH and Slovak Academy of Sciences, Austria ; 3 Institute of Measurement Science, Slovak Republic

ISBN: 978-989-8565-41-9

Keyword(s): Anomaly Face Classification, Hierarchical Temporal Memory, Automatic Teller Machine, Kinect, Surveillance System.

Related Ontology Subjects/Areas/Topics: Applications ; Bioinformatics and Systems Biology ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Object Recognition ; Pattern Recognition ; Software Engineering ; Video Analysis

Abstract: The aim of this paper is to report on a pilot application of a bio-inspired intelligent network model, called Hierarchical Temporal Memory (HTM), for recognition (detection) of untrustworthy manipulation with an Automatic Teller Machine (ATM). HTM was used as a crucial part of an anomaly detection system to recognize hard-to-identifiable faces, i.e., faces with a mask, covered with a scarf, or wearing sunglasses. Those types of face occlusion can be a good indicator of potentialy malicious intentions of an ATM user. In the presented system, the Kinect camera was used for acquisition of video image sequences. The Kinect’s depth output along with skeleton tracking was used as a basis of the color image segmentation. To test the proposed system, experiments have been carried out in which several participants performed normal and untrustworthy actions using an ATM simulator. The output of the face classification system can assist a security personnel in surveillance tasks.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.207.134.98

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Škoviera, R.; Valentín, K.; Štolc, S. and Bajla, I. (2013). Recognition of Untrustworthy Face Images in ATM Sessions using a Bio-inspired Intelligent Network.In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 511-517. DOI: 10.5220/0004195605110517

@conference{icpram13,
author={R. Škoviera. and K. Valentín. and S. Štolc. and I. Bajla.},
title={Recognition of Untrustworthy Face Images in ATM Sessions using a Bio-inspired Intelligent Network},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2013},
pages={511-517},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004195605110517},
isbn={978-989-8565-41-9},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Recognition of Untrustworthy Face Images in ATM Sessions using a Bio-inspired Intelligent Network
SN - 978-989-8565-41-9
AU - Škoviera, R.
AU - Valentín, K.
AU - Štolc, S.
AU - Bajla, I.
PY - 2013
SP - 511
EP - 517
DO - 10.5220/0004195605110517

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.