Abstract
Using electroencephalogram meters to assess students’ attention level and to figure out possible problems and solutions is an emerging research direction. However, the major challenge is the cost of adopting electroencephalogram meters that is simply too high. In this research, we propose to use cameras instead. With the advancements of expression recognition technologies, the detection rate of basic emotions is promising. With such a method, we can assist lecturers by issuing warnings for students with low attention levels. We designed an algorithm that can investigate students’ attention level based on the change rate of the location of their face landmarks. In the manuscript, we proposed the algorithm and the implementation along with experiment results.
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Tseng, CH., Chen, YH. A camera-based attention level assessment tool designed for classroom usage. J Supercomput 74, 5889–5902 (2018). https://doi.org/10.1007/s11227-017-2122-7
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DOI: https://doi.org/10.1007/s11227-017-2122-7