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Title: A new approach for pain event detection in video
Authors: Chen, J
Chi, Z 
Fu, H
Keywords: HOG-TOP
Pain event detection
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers
Source: 2015 International Conference on Affective Computing and Intelligent Interaction (ACII), Xi'an, China, 21-24 Sept 2015, p.250-254 How to cite?
Abstract: A new approach for pain event detection in video is presented in this paper. Different from some previous works which focused on frame-based detection, we target in detecting pain events at video level. In this work, we explore the spatial information of video frames and dynamic textures of video sequences, and propose two different types of features. HOG of fiducial points (P-HOG) is employed to extract spatial features from video frames and HOG from Three Orthogonal Planes (HOG-TOP) is used to represent dynamic textures of video subsequences. After that, we apply max pooling to represent a video sequence as a global feature vector. Multiple Kernel Learning (MKL) is utilized to find an optimal fusion of the two types of features. And an SVM with multiple kernels is trained to perform the final classification. We conduct our experiments on the UNBC-McMaster Shoulder Pain dataset and achieve promising results, showing the effectiveness of our approach.
ISBN: 978-1-4799-9953-8 (electronic)
978-1-4799-9952-1 (USB)
978-1-4799-9954-5 (print on demand(PoD))
ISSN: 2156-8111
DOI: 10.1109/ACII.2015.7344579
Appears in Collections:Conference Paper

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