NDLI: Face template creation: Is Centroid Method a suitable approach?

Content Provider	IEEE Xplore Digital Library
Author	Malach, T. Pomenkova, J.
Copyright Year	2014
Description	Author affiliation: Dept. of Radio Electron., Brno Univ. of Technol., Brno, Czech Republic (Malach, T.; Pomenkova, J.)
Abstract	The paper presents a research and development of a face template creation sub-system, which serves a part of a face-based identification system. This system is intended to be used in surveillance camera systems. The paper addresses a problem of contradicting requirements on the face recognition system - near-real time recognition and a low error rate. The research, we have conducted, has shown that a solution may be found in designing an adequate face template database and in applying appropriate face template creation algorithms. Face templates have a significant influence on the correct classification rate, while the number of temples is directly proportional to the classification time. The results of our research have so far proved that using the Centroid Method for face templates creation is the best performing approach. The paper presents two novel methods for a face template creation in order to investigate whether the Centroid Method may be outperformed. The performance of proposed face template methods is evaluated on images from an extensive IFaViD database assembled during our research, images were captured by a surveillance camera system.
Sponsorship	IEEE Czechoslovakia Sect.
Starting Page	1
Ending Page	4
File Size	366049
Page Count	4
File Format	PDF
ISBN	9781479937141
e-ISBN	9781479937158
DOI	10.1109/Radioelek.2014.6828428
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-04-15
Publisher Place	Slovakia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training real-word conditions Databases Face recognition Surveillance face template database face templates face recognition Cameras Vectors Face
Content Type	Text
Resource Type	Article

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