Title :
Modeling Stress Using Thermal Facial Patterns: A Spatio-temporal Approach
Author :
Sharma, Neelam ; Dhall, Abhinav ; Gedeon, Tom ; Goecke, Roland
Author_Institution :
iHCC Group, Australian Nat. Univ., Canberra, ACT, Australia
Abstract :
Stress is a serious concern facing our world today, motivating the development of better objective understanding using non-intrusive means for stress recognition. The aim for the work was to use thermal imaging of facial regions to detect stress automatically. The work uses facial regions captured in videos in thermal (TS) and visible (VS) spectrums and introduces our database ANU StressDB. It describes the experiment conducted for acquiring TS and VS videos of observers of stressed and not-stressed films for the ANU StressDB. Further, it presents an application of local binary patterns on three orthogonal planes (LBP-TOP) on VS and TS videos for stress recognition. It proposes a novel method to capture dynamic thermal patterns in histograms (HDTP) to utilize thermal and spatio-temporal characteristics associated in TS videos. Individual-independent support vector machine classifiers were developed for stress recognition. Results show that a fusion of facial patterns from VS and TS videos produced significantly better stress recognition rates than patterns from only VS or TS videos with p <; 0.01. The best stress recognition rate was 72% and it was obtained from HDTP features fused with LBP-TOP features for TS and VS videos respectively.
Keywords :
emotion recognition; face recognition; image classification; infrared imaging; support vector machines; visual databases; ANU StressDB; HDTP; TS videos; VS videos; automatic stress detection; dynamic thermal patterns in histograms; facial patterns fusion; facial regions; individual-independent support vector machine classifiers; local binary patterns; spatio-temporal approach; stress modeling; stress recognition; thermal facial patterns; thermal imaging; thermal spectrums; visible spectrums; Computational modeling; Face recognition; Sensors; Stress; Support vector machines; Thermal stresses; Videos; Stress classification; database; thermal analysis; visual analysis;
Conference_Titel :
Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on
Conference_Location :
Geneva
DOI :
10.1109/ACII.2013.70