Evaluation of head pose features for stress detection and classification

This paper investigates variations in head pose features in response to specific stressors. A proper experiment consisting of neutral and stressful states was performed aiming to cover different types of stress affect. Then, features related to head movements and pose were computationally estimated and analyzed. Towards this direction, facial landmarks were fitted using Active Appearance Models (AAM). Using the 2D AAM facial landmarks, a 3D head pose model was estimated revealing head inclinations. Results indicate that specific stress conditions increase head mobility and mobility velocity, in both translational and rotational features. Even though stress modulates head movements and velocities, the most prominent increases are presented during tasks that include participant's speech. The degree and the intensity of the interaction effect between speech and stress should be investigated in more detail. The analysis reports that specific head pose features can be significant stress indicators that could contribute among other facial cues in reliable stress recognition.

[1]  Mohan M. Trivedi,et al.  Head Pose Estimation and Augmented Reality Tracking: An Integrated System and Evaluation for Monitoring Driver Awareness , 2010, IEEE Transactions on Intelligent Transportation Systems.

[2]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[3]  Simon Baker,et al.  Active Appearance Models Revisited , 2004, International Journal of Computer Vision.

[4]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[5]  Frédo Durand,et al.  Detecting Pulse from Head Motions in Video , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[6]  Manolis Tsiknakis,et al.  Stress and anxiety detection using facial cues from videos , 2017, Biomed. Signal Process. Control..

[7]  K. Scherer,et al.  Bodily expression of emotion , 2009 .

[8]  Dimitris N. Metaxas,et al.  Optical computer recognition of facial expressions associated with stress induced by performance demands. , 2005, Aviation, space, and environmental medicine.

[9]  Jeffrey F. Cohn,et al.  What can head and facial movements convey about positive and negative affect? , 2015, 2015 International Conference on Affective Computing and Intelligent Interaction (ACII).

[10]  U. Hadar,et al.  Head Movement Correlates of Juncture and Stress at Sentence Level , 1983, Language and speech.

[11]  Larry S. Davis,et al.  Model-based object pose in 25 lines of code , 1992, International Journal of Computer Vision.

[12]  Michael Wagner,et al.  Head Pose and Movement Analysis as an Indicator of Depression , 2013, 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction.

[13]  Mohan M. Trivedi,et al.  Head Pose Estimation in Computer Vision: A Survey , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Josef Kittler,et al.  Floating search methods in feature selection , 1994, Pattern Recognit. Lett..

[15]  Zhiwei Zhu,et al.  A Real-Time Human Stress Monitoring System Using Dynamic Bayesian Network , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[16]  Thomas B. Moeslund,et al.  Improved pulse detection from head motions using DCT , 2014, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

[17]  Rae-Hong Park,et al.  Head pose estimation using a coplanar face model for human computer interaction , 2014, 2014 IEEE International Conference on Consumer Electronics (ICCE).

[18]  Kun Liu,et al.  Attention recognition of drivers based on head pose estimation , 2008, 2008 IEEE Vehicle Power and Propulsion Conference.

[19]  Bogdan J. Matuszewski,et al.  Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system , 2016, Comput. Vis. Image Underst..

[20]  Peter Robinson,et al.  Decoupling facial expressions and head motions in complex emotions , 2015, 2015 International Conference on Affective Computing and Intelligent Interaction (ACII).