You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
10 February 2009Eye blink detection based on eye contour extraction
Eye blink detection is one of the important problems in computer vision. It has many applications such as face live
detection and driver fatigue analysis. The existing methods towards eye blink detection can be roughly divided into two
categories: contour template based and appearance based methods. The former one usually can extract eye contours
accurately. However, different templates should be involved for the closed and open eyes separately. These methods are
also sensitive to illumination changes. In the appearance based methods, image patches of open-eyes and closed-eyes are
collected as positive and negative samples to learn a classifier, but eye contours can not be accurately extracted. To
overcome drawbacks of the existing methods, this paper proposes an effective eye blink detection method based on an
improved eye contour extraction technique. In our method, eye contour model is represented by 16 landmarks therefore
it can describe both open and closed eyes. Each landmark is accurately recognized by fast classifier which is trained from
the appearance around this landmark. Experiments have been conducted on YALE and another large data set consisting
of frontal face images to extract the eye contour. The experimental results show that the proposed method is capable of
affording accurate eye location and robust in closed eye condition. It also performs well in the case of illumination
variants. The average time cost of our method is about 140ms on Pentium IV 2.8GHz PC 1G RAM, which satisfies the
real-time requirement for face video sequences. This method is also applied in a face live detection system and the
results are promising.
The alert did not successfully save. Please try again later.
Liting Wang, Xiaoqing Ding, Chi Fang, Changsong Liu, Kongqiao Wang, "Eye blink detection based on eye contour extraction," Proc. SPIE 7245, Image Processing: Algorithms and Systems VII, 72450R (10 February 2009); https://doi.org/10.1117/12.804916