Abstract
In this study, a novel approach for continuous pain intensity estimation based on facial feature deformations is presented. The proposed approach is based on the fact that the shape and appearance of facial features get deformed due to pain. The shape deformation caused due to pain is computed using Thin Plate Spline (TPS). The non-rigid parameters are used as representative of facial feature deformations and affine transformation parameters are ignored. The deformation of appearance features is extracted using local binary pattern features. The shape and appearance features are fed to relevance vector regression separately and jointly for pain intensity estimation. The pain intensity estimation is carried directly (by estimating the pain intensity from facial feature deformation) and indirectly by first estimating the Action Unit intensity and then computing the pain intensity. For assessment of the proposed approach, we have selected the popularly accepted UNBC-McMaster Shoulder Pain Expression Archive Database. Experimental results ensure the efficacy of the proposed approach for pain intensity estimation.
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Neeru Rathee, Dinesh Ganotra (2017). A Novel Approach for Continuous Pain Intensity Estimation. In: Singh, R., Choudhury, S. (eds) Proceeding of International Conference on Intelligent Communication, Control and Devices . Advances in Intelligent Systems and Computing, vol 479. Springer, Singapore. https://doi.org/10.1007/978-981-10-1708-7_50
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DOI: https://doi.org/10.1007/978-981-10-1708-7_50
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