Cognitive Behaviour Analysis Based on Facial Information Using Depth Sensors [chapter]

Juan Manuel Fernandez Montenegro, Barbara Villarini, Athanasios Gkelias, Vasileios Argyriou
<span title="">2018</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Cognitive behaviour analysis is considered of high importance with many innovative applications in a range of sectors including healthcare, education, robotics and entertainment. In healthcare, cognitive and emotional behaviour analysis helps to improve the quality of life of patients and their families. Amongst all the different approaches for cognitive behaviour analysis, significant work has been focused on emotion analysis through facial expressions using depth and EEG data. Our work
more &raquo; ... ces an emotion recognition approach using facial expressions based on depth data and landmarks. A novel dataset was created that triggers emotions from long or short term memories. This work uses novel features based on a non-linear dimensionality reduction, t-SNE, applied on facial landmarks and depth data. Its performance was evaluated in a comparative study, proving that our approach outperforms other state-of-the-art features.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-91863-1_2">doi:10.1007/978-3-319-91863-1_2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vzdlsnybazgtrolc5uscqi5qya">fatcat:vzdlsnybazgtrolc5uscqi5qya</a> </span>
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