NDLI: Pain intensity recognition via multi-scale deep network

Content Provider	IET Digital Library
Author	Peng, Xianlin Huang, Dong Zhang, Haixi
Abstract	Similar to the basic facial expression recognition, one challenge for pain intensity recognition is some individual characteristics, e.g. face shapes, may cause great diversities in the same emotion. So it is usually very difficult to distinguish two adjacent intensity levels of pain expression as each intensity has a large variation. In this study, a coarse-to-fine combination method is proposed for pain intensity recognition. The results of multi-scale outputs from multiple base deep network are combined in a probabilistic way for improving the discrimination between visually similar adjacent levels. A two-layer tree classifier is proposed in a multi-task framework for pain intensity recognition as well as face shape recognition, replacing the planar Softmax classifier in each base deep network. In the first layer of tree classifier, multi-scale classifiers are constructed for recognizing facial pain intensities and the conventional classifiers are constructed for face shape recognition in the second layer. Finally, the tree classifier including multi-scale classifiers and conventional classifiers is jointly optimised during the training phase and only high level classifiers are used for recognising pain intensities in the test phase. The extensive experiments on UNBC shoulder pain dataset show the proposed method gets promising results in pain intensity recognition.
Starting Page	1645
Ending Page	1652
Page Count	8
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 8, Jun (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.1448
Journal	IET Image Processing
Publisher Date	2020-04-02
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adjacent Intensity Levels Basic Facial Expression Recognition Computer Vision And Image Processing Technique Emotion Recognition Face Recognition Face Shape Recognition Facial Pain Intensities Feature Extraction Image Classification Image Recognition Image Sequence Knowledge Engineering Technique Learning in AI Multiscale Deep Network Optical, Image And Video Signal Processing Pain Intensity Recognition Pattern Classification Statistics Tree Classifier Including Multiscale Classifier Video Signal Processing
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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