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
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.