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Human motion distribution learning from face images using CNN and LBC features

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Almowallad, Abeer and Sanchez Silva, Victor (2020) Human motion distribution learning from face images using CNN and LBC features. In: The 8th International Workshop on Biometrics and Forensics (IWBF-2020), Porto, Portugal, 29-30 Apr 2020. Published in: 2020 8th International Workshop on Biometrics and Forensics (IWBF) ISBN 9781728162331. doi:10.1109/IWBF49977.2020.9107940

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Official URL: https://doi.org/10.1109/IWBF49977.2020.9107940

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Abstract

Human emotion recognition from facial expressions depicted in images is an active area of research particularly for medical, security and human-computer interaction applications. Since there is no pure emotion, measuring the intensity of several possible emotions depicted in a facial expression image is a challenging task. Previous studies have dealt with this challenge by using label-distribution learning (LDL) and focusing on optimizing a conditional probability function that attempts to reduce the relative entropy of the predicted distribution with respect to the target distribution, which leads to a lack of generality of the model. In this work, we propose a deep learning framework for LDL that uses convolutional neural network (CNN) features to increase the generalization of the trained model. Our framework, which we call EDL-LBCNN, enhances the features extracted by CNNs by incorporating a local binary convolutional (LBC) layer to acquire texture information from the face images. We evaluate our EDL-LBCNN framework on the s-JAFFE dataset. Our experimental results show that the EDL- LBCNN framework can effectively deal with LDL for human emotion recognition and attain a stronger performance than that of state-of-the-art methods.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Human face recognition (Computer science), Emotion recognition -- Computer programs, Facial expression, Neural networks (Computer science), Diagnostic imaging -- Data processing, Face -- Computer simulation
Journal or Publication Title: 2020 8th International Workshop on Biometrics and Forensics (IWBF)
Publisher: IEEE
ISBN: 9781728162331
Official Date: 4 June 2020
Dates:
DateEvent
4 June 2020Published
9 March 2020Accepted
DOI: 10.1109/IWBF49977.2020.9107940
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 21 May 2020
Date of first compliant Open Access: 22 May 2020
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDTaif Universityhttp://dx.doi.org/10.13039/501100006261
UNSPECIFIEDSaudi Arabia. Idārat al-Āthār wa-al-Matāḥif)http://viaf.org/viaf/138915155
Conference Paper Type: Paper
Title of Event: The 8th International Workshop on Biometrics and Forensics (IWBF-2020)
Type of Event: Workshop
Location of Event: Porto, Portugal
Date(s) of Event: 29-30 Apr 2020
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