Gaze tracking with particle swarm optimization

Author

Wen-Chung Kao ; Chia-Yi Lee ; Chun-Yi Lin ; Ting-Yi Su ; Bai-Yueh Ke ; Chung-Yu Liao

Author_Institution

Dept. Electr. Eng., Nat. Taiwan Normal Univ., Taipei, Taiwan

fYear

2015

fDate

24-26 June 2015

Firstpage

1

Lastpage

2

Abstract

In order to develop the next generation of gaze tracking system that can operate under visible lighting conditions, the difficulty of estimating limbus circle in real time needs to be solved. The iris model-based approaches excel the feature-based ones, but high computation complexity remains a problem. This paper presents an advanced iris model-based matching algorithm which adopts particle swarm optimization (PSO) to improve the overall performance. As a result, the developed system achieves high accuracy and the objective of 30 frames.

Keywords

computational complexity; gaze tracking; image matching; iris recognition; particle swarm optimisation; advanced iris model-based matching algorithm; computation complexity; gaze tracking; iris model-based approaches; limbus circle; particle swarm optimization; visible lighting conditions; Accuracy; Feature extraction; Fitting; Gaze tracking; Iris; Particle swarm optimization; Signal processing algorithms; gaze tracking; iris matching; particle swarm optimization (PSO);

fLanguage

English

Publisher

ieee

Conference_Titel

Consumer Electronics (ISCE), 2015 IEEE International Symposium on

Conference_Location

Madrid

Type

conf

DOI

10.1109/ISCE.2015.7177836

Filename

7177836