A method of iris tracking based on machine vision

DOI

10.2991/iccsee.2013.241How to use a DOI?

Keywords

iris tracking, template matching, Kalman filter, Mean Shift algorithm

Abstract

Through analyzing the advantages and disadvantages of the template matching method, Kalman Filter and Mean Shift algorithm, we proposed the method of combining them. We use the template matching method to initialize the irises positions, extract the eyes area, and then combined Kalman filter with Mean Shift algorithm to position and track irises accurately. The method also added to the average speed of the targets, it not only could be used as the standard if the irises are affected by the background, but also could be used as the irises speed when eyes are blocked, and then forecast the goals possible area in the next frame. This method is able to overcome the problems about irises tracking failure when there are tilt angle, deflection angle and pitch angle of the head in a certain range, and the object occlusion and background interference problems, which compressed the amount of computation and improved robustness of the iris tracking.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Dong-shuang Li
AU  - Lan-xiang Zhong
PY  - 2013/03
DA  - 2013/03
TI  - A method of iris tracking based on machine vision
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 956
EP  - 959
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.241
DO  - 10.2991/iccsee.2013.241
ID  - Li2013/03
ER  -