Spatiotemporal Smoothing as a Basis for Facial Tissue Tracking in Thermal Imaging

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 paper presents a particle filter tracker driven by a probabilistic template function with both spatial and temporal smoothing...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2013-05, Vol.60 (5), p.1280-1289
Main Authors: Zhou, Yan, Tsiamyrtzis, Panagiotis, Lindner, Peggy, Timofeyev, Ilya, Pavlidis, Ioannis
Format: Article
Language:English
Subjects:
Algorithms
Cost function
Databases, Factual
Face - physiology
Facial tracking
Head Movements - physiology
Humans
Imaging
Infrared Rays
matte
Physiology
Signal Processing, Computer-Assisted
sleep studies
Stress
stress studies
Target tracking
thermal imaging
Thermography - methods
Visualization
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Summary: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 paper 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 25 thermal clips. It demonstrated robustness and accuracy, outperforming other strategies. This new method promises improved performance in a number of biomedical applications that involve physiological measurements on the face, such as unobtrusive sleep and stress studies.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2012.2232927