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Keeping students attentive during lectures may significantly improve learning outcomes. Traditional methods of attention estimation cannot offer a real-time feedback to the teacher. We present a technical concept of student attention monitoring during a lecture. The system utilizes a set of cameras providing tracking of the behavior of individual students in the classroom. The monitoring system is...
This paper presents an experimental study on the real-time estimation of observed learners’ attention given the task of touch-typing. The aim is to examine whether the observed attention estimates gathered from human raters can be computationally modeled in real time, based on the learner’s psychophysiological and affective signals. A key observation from this paper is that the observed attention...
Affective labeling of multimedia content has proved to be useful in recommender systems. In this paper we present a methodology for the implicit acquisition of affective labels for images. It is based on an emotion detection technique that takes as input the video sequences of the users' facial expressions. It extracts Gabor low level features from the video frames and employs a k nearest neighbors...
Recent work has shown an increase of accuracy in recommender systems that use affective labels. In this paper we compare three labeling methods within a recommender system for images: (i) generic labeling, (ii) explicit affective labeling and (iii) implicit affective labeling. The results show that the recommender system performs best when explicit labels are used. However, implicitly acquired labels...
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