Automatic Detection of Naturalistic Hand-over-Face Gesture Descriptors

Marwa M. Mahmoud, Tadas Baltrušaitis, Peter Robinson
2014 Proceedings of the 16th International Conference on Multimodal Interaction - ICMI '14  
One of the main factors that limit the accuracy of facial analysis systems is hand occlusion. As the face becomes occluded, facial features are either lost, corrupted or erroneously detected. Hand-over-face occlusions are considered not only very common but also very challenging to handle. Moreover, there is empirical evidence that some of these hand-over-face gestures serve as cues for recognition of cognitive mental states. In this paper, we detect hand-over-face occlusions and classify
more » ... ver-face gesture descriptors in videos of natural expressions using multi-modal fusion of different state-of-the-art spatial and spatio-temporal features. We show experimentally that we can successfully detect face occlusions with an accuracy of 83%. We also demonstrate that we can classify gesture descriptors (hand shape, hand action and facial region occluded ) significantly higher than a naïve baseline. To our knowledge, this work is the first attempt to automatically detect and classify hand-over-face gestures in natural expressions.
doi:10.1145/2663204.2663258 dblp:conf/icmi/MahmoudB014 fatcat:a2wqdabuxffy5pisutsc56phhe