TY  - JOUR
T1  - Automatic Recognition of Cognitive States Using Multimodal
Approaches in e-Learning Environments
AU - Gunavathi, H.S. AU - Siddappa, M. 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 4
SP  - 1286
EP  - 1294
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.1286.1294
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.1286.1294
KW  - Cognitive states
KW  -compressive sensing
KW  -facial expressions
KW  -hand-over face gesture
KW  -robust
KW  -hand
AB  - Cognitive state recognition is one of the active science researches all around the world and it has
grown spontaneously in recent years. However, most research focuses on posed expressions, near frontal
recordings and they ignore eye gaze, head pose and considers hand occlusions as noise. It makes tough to tell
how the existing methods perform underneath conditions where faces appear in a wide range of poses and
occluded by hands. In this study, we propose multimodal approaches for building a real-time cognitive state
recognition system in e-Learning environments by integrating hand-over-face gesture with facial expression.
Our proposed system performs an average recognition rate of 90.51% with 15.8 fps is robust to variations in
facial expressions, hand shapes and occlusions.
ER  -