Tissue tracking in thermo-physiological imagery through spatio-temporal smoothing.
Accurate tracking of facial tissue in thermal infrared imaging is challenging because it is affected not only by positional but also physiological (functional) changes. This article presents a particle filter tracker driven by a probabilistic template function with both spatial and temporal smoothing components, which is capable of adapting to abrupt positional and physiological changes. The method was tested on tracking facial regions of subjects under varying physiological and environmental conditions in 12 thermal clips. It demonstrated robustness and accuracy, outperforming other strategies. This new method promises improved performance in a host of biomedical applications that involve physiological measurements on the face, like unobtrusive sleep studies.
Zhou
Yan
Y
Department of Computer Science, University of Houston, Houston, TX 77024, USA. yzhou9@uh.edu
Tsiamyrtzis
Panagiotis
P
Pavlidis
Ioannis T
IT
D000465:Algorithms; D005145:Face / Q000033:anatomy & histology* / Q000502:physiology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013817:Thermography / Q000379:methods*