A general approach to connected-component labeling for arbitrary image representations
Journal of the ACM (JACM)
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 5 - Volume 05
Pose-Invariant Physiological Face Recognition in the Thermal Infrared Spectrum
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Imaging Facial Physiology for the Detection of Deceit
International Journal of Computer Vision
Computer Vision and Image Understanding
Eye localization from infrared thermal images
MPRSS'12 Proceedings of the First international conference on Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction
Eye localization from thermal infrared images
Pattern Recognition
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User intervention in the periorbital thermal signal extraction process breaks down automation. This paper proposes a novel way to minimize user intervention. While previous work demonstrated the importance of accurate computation of the periorbital signal, the present method enables its automatic extraction at a reduced processing time. The proposed algorithm capitalizes on detection of involuntary eye blinking in the thermal imagery. The need for automation has emerged because of repetitive processing of the same subjects, aiming to validate improvements in the periorbital tissue tracking or segmentation algorithms. The proposed approach initiates the tracking and segmentation algorithms on the same spatio-temporal location in repetitive runs of the thermal clip. Thus, it does not only automate the process but also eliminates the variability introduced by manual intervention. We have tested the algorithm on thermal video clips of 39 subjects who faced stressful interrogation for a mock crime. The results show that the proposed method has reduced total processing time from a week down to a day.