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.
['Dvijesh Shastri', 'Ioannis T. Pavlidis']
Automatic Initiation of the Periorbital Signal Extraction in Thermal Imagery