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Robust Eye and Pupil Detection Method for Gaze Tracking : Riconoscimento robusto di occhio e pupilla per tracking, in: International Journal of Advanced Robotic Systems |
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Author |
Gwon, Su Yeong; Cho, Chul Woo; Lee, Hyeon Chang; Lee, Won Oh; Park, Kang Ryoung |
Published |
InTech Open Access Publisher, 2013
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Abstract |
Robust and accurate pupil detection is a
prerequisite for gaze detection. Hence, we propose a
new eye/pupil detection method for gaze detection on a
large display. The novelty of our research can be
summarized by the following four points. First, in order
to overcome the performance limitations of
conventional methods of eye detection, such as adaptive
boosting (Adaboost) and continuously adaptive mean
shift (CAMShift) algorithms, we propose adaptive
selection of the Adaboost and CAMShift methods.
Second, this adaptive selection is based on two
parameters: pixel differences in successive images and
matching values determined by CAMShift. Third, a
support vector machine (SVM)‐based classifier is used
with these two parameters as the input, which improves
the eye detection performance. Fourth, the center of the
pupil within the detected eye region is accurately
located by means of circular edge detection, binarization
and calculation of the geometric center.
The experimental results show that the proposed method
can detect the center of the pupil at a speed of
approximately 19.4 frames/s with an RMS error of
approximately 5.75 pixels, which is superior to the
performance of conventional detection methods. |
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International Journal of Advanced Robotic Systems
Author: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Published: 2004
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