Learning Pain from Emotion: Transferred HoT Data Representation for Pain Intensity Estimation

被引：39

作者：

Florea, Corneliu ^{[1
]}

Florea, Laura ^{[1
]}

Vertan, Constantin ^{[1
]}

机构：

[1] Univ Politehn Bucuresti, Image Proc & Anal Lab, Bucharest, Romania

来源：

COMPUTER VISION - ECCV 2014 WORKSHOPS, PT III | 2015年 / 8927卷

关键词：

Histograms of Topographical features (HoT); Spectral regression; Transfer learning; Pain intensity estimation; EXPRESSION RECOGNITION; SCALE;

D O I：

10.1007/978-3-319-16199-0_54

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Automatic monitoring for the assessment of pain can significantly improve the psychological comfort of patients. Recently introduced databases with expert annotation opened the way for pain intensity estimation from facial analysis. In this contribution, pivotal face elements are identified using the Histograms of Topographical features (HoT) which are a generalization of the topographical primal sketch. In order to improve the discrimination between different pain intensity values and respectively the generalization with respect to the monitored persons, we transfer data representation from the emotion oriented Cohn-Kanade database to the UNBC McMaster Shoulder Pain database.

引用

页码：778 / 790

页数：13

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