A real-time non-intrusive attention tracking system using a simple web camera is proposed in this paper. This system is scale and rotation invariant and tolerant to blink related false attention state classifications. Attention states of the students are classified into three: attentive, sleepy and disappeared. A simple geometric model for eye corners detection is proposed. Active and passive attention tracking experiments are conducted with a 54 minutes video lecture as the e-learning session content. Experimental results show that the proposed system clearly discriminates the attention states of the student participated in the E-learning session. The execution time of the proposed algorithm is 10 milliseconds per image frame. The proposed system is highly suitable for real-time applications. © 2012 IEEE.
cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@5f7b79e ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@4a37e921 Through org.apache.xalan.xsltc.dom.DOMAdapter@1caa9b98; Conference Code:90662
S. Aa Narayanan, Prasanth, Ma, Mohan, Pa, Kaimal, M. Rb, and Bijlani, Ka, “Attention analysis in e-learning environment using a simple web camera”, in Proceedings - 2012 IEEE International Conference on Technology Enhanced Education, ICTEE 2012, Kerala, 2012.