University of Oulu

Tran, T.-K., Vo, Q.-N., Hong, X., & Zhao, G. (2019). Dense prediction for micro-expression spotting based on deep sequence model. Electronic Imaging, 2019(8), 401-1-401–406. https://doi.org/10.2352/issn.2470-1173.2019.8.imawm-401

Dense prediction for micro-expression spotting based on deep sequence model

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Author: Tran, Thuong-Khanh1; Vo, Quang-Nhat1; Hong, Xiaopeng1;
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu; Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020042722471
Language: English
Published: Society for Imaging Science & Technology, 2019
Publish Date: 2020-04-27
Description:

Abstract

Micro-expression (ME) analysis has been becoming an attractive topic recently. Nevertheless, the studies of ME mostly focus on the recognition task while spotting task is rarely touched. While micro-expression recognition methods have obtained the promising results by applying deep learning techniques, the performance of the ME spotting task still needs to be largely improved. Most of the approaches still rely upon traditional techniques such as distance measurement between handcrafted features of frames which are not robust enough in detecting ME locations correctly. In this paper, we propose a novel method for ME spotting based on a deep sequence model. Our framework consists of two main steps: 1) From each position of video, we extract a spatial-temporal feature that can discriminate MEs among extrinsic movements. 2) We propose to use a LSTM network that can utilize both local and global correlation of the extracted feature to predict the score of the ME apex frame. The experiments on two publicly databases of ME spotting demonstrate the effectiveness of our proposed method.

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Series: IS&T International Symposium on Electronic Imaging
ISSN: 2470-1173
ISSN-E: 2470-1173
ISSN-L: 2470-1173
Pages: 401-1 - 401-6(6)
DOI: 10.2352/ISSN.2470-1173.2019.8.IMAWM-401
OADOI: https://oadoi.org/10.2352/ISSN.2470-1173.2019.8.IMAWM-401
Host publication: IS&T International Symposium on Electronic Imaging: Science and technology, Imaging and Multimedia Analytics in a Web and Mobile World 2019. 13-17 Janyuary 2019, Burlingame, USA
Host publication editor: Allebach, Jan P.
Fan, Zhipang
Lin, Qian
Conference: IS&T International Symposium on Electronic Imaging
Type of Publication: B3 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Funding: This work was supported by the Academy of Finland, Tekes Fidipro program (Grant No. 1849/31/2015), Business Finland project (Grant No. 3116/31/2017), and Infotech Oulu.
Academy of Finland Grant Number: 1849/31
Detailed Information: 1849/31 (Academy of Finland Funding decision)
Copyright information: © 2019, Society for Imaging Science and Technology. Reprinted with permission of IS&T: The Society for Imaging Science and Technology sole copyright owners of the Electronic Imaging, Imaging and Multimedia Analytics in a Web and Mobile World 2019.