Video-Based Eye Tracking to Detect the Attention Shift: A Computer Classroom Context-Aware System

Video-Based Eye Tracking to Detect the Attention Shift: A Computer Classroom Context-Aware System

Yung-Lung Kuo (Department of Computer Science and Information Engineering, Far East University, Tainan, Taiwan), Jiann-Shu Lee (Department of Computer Science and Information Engineering, National University of Tainan, Tainan, Taiwan) and Min-Chai Hsieh (Department of Information Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan)
Copyright: © 2014 |Pages: 16
DOI: 10.4018/ijdet.2014100105
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Eye and head movements evoked in response to obvious visual attention shifts. However, there has been little progress on the causes of absent-mindedness so far. The paper proposes an attention awareness system that captures the conditions regarding the interaction of eye gaze and head pose under various attentional switching in computer classroom. Via the algorithm of complexion area detection, eye location and eye tracking, the system detects the shifts of the subject's attention, records it and sends a notification to the class teacher. In five variant experiments of attentional shift, the authors find the cues of subjects when turning to other directions, moving forwards or backwards, and closing eyes. It applies even if the students wear glasses or have hair fringe. The findings of absent-mindedness are very important for psychologists or educators conducting post-hoc analysis. These experimental results show eye tracking are useful for detecting shift of attention.
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1. Introduction

Eyes are one of the most prominent features of the human face. Not only are the unique geometric characteristic eyes treated as a biometric authentication. Therefore, many applications focusing on eye shift detection or eye tracking have been proposed in recent years, such as attention tracking (Riby & Hancock, 2009), driver fatigue detection (Horng, Chen & Chang, 2004; Yang & Bhattacharya, 2010; Dong, Uchimura & Murayama, 2011), marketing research (Pieters & Wedel, 2004; Pieters & Wedel, 2007) and neurological diagnosis (Maruko, Lida, Sugano, Olima, Oqasawara & Spaide, 2010). Besides, eye motion and perception of concentration also provide important information about the quality or state of sentiment. So far, many researchers have been studied for activity recognition Bulling, Ward, Gellersen & Troster, 2011; Sauppe, Norcliffe, Konopka, Van Valin Jr & Levinson, 2013) and attention disengagement (Sanchez, Vazquez, Marker & LeMoult, 2013) by using eye-tracking technique. A variety of indoor sports also can be identified by using special sensors (Logan, Healey, Philipose, Tapia & Intille, 2007; Fogarty, Au & Hudson, 2006). In order to obtain information about which element the observer’s attention is drawn to, researchers often need construct nonintrusive system for eye detection and tracking system. They have shown that enough information about gaze shift is quite helpful for understanding absent-mindedness of the subject.

Eye tracking is a technique about observing eyes gazing or measuring the motion of eyes relative to the head. Tracking systems are usually equipped with an eye tracker (eye tracking device) for measuring the position or motion of the eye. Some also need other auxiliaries, including special lenses or sensing elements of electric potentials. As usual, eye movement reflects the human thought process, and closely correlates with attentiveness. This promotes researchers to detect the switching of attention by measuring eye moving. One method of measuring eye movement is using the electrodes. Typically they are placed either above and below the eye or to the left and right of the eye. When the eye moves form center position toward one electrode, a potential difference occurs. The technique about measuring the signal of electrodes is called Electrooculography (EOG). Although EOG is a cheap method and computationally light-weight for mobile eye movement recordings, it still causes the subject's inconvenient (Satel, Hassall, Krigolson & Klein, 2013). One of the most popular variant was temporal difference method, which determined shift by retrieving the position of the eyes at current frame and making a comparison with the eye position extracted in previous frame. Such experiments use no additional attachments, eliminating the discomfort of the observed.

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