University of Oulu

Tran TK., Hong X., Zhao G. (2017) Sliding Window Based Micro-expression Spotting: A Benchmark. In: Blanc-Talon J., Penne R., Philips W., Popescu D., Scheunders P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2017. Lecture Notes in Computer Science, vol 10617. Springer, Cham

Sliding window based micro-expression spotting : a benchmark

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Author: Tran, Thuong-Khanh1; Hong, Xiaopeng1; Zhao, Guoying1
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.2 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2017120155190
Language: English
Published: Springer Nature, 2017
Publish Date: 2017-12-01
Description:

Abstract

Micro-expressions are very rapid and involuntary facial expressions, which indicate the suppressed or concealed emotions and can lead to many potential applications. Recently, research in micro-expression spotting obtains increasing attention. By investigating existing methods, we realize that evaluation standards of micro-expression spotting methods are highly desired. To address this issue, we construct a benchmark for fairer and better performance evaluation of micro-expression spotting approaches. Firstly, we propose a sliding window based multi-scale evaluation standard with a series of protocols. Secondly, baseline results of popular features are provided. Finally, we also raise the concerns of taking advantages of machine learning techniques.

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Series: Lecture notes in computer science
ISSN: 0302-9743
ISSN-E: 1611-3349
ISSN-L: 0302-9743
ISBN: 978-3-319-70353-4
ISBN Print: 978-3-319-70352-7
Issue: 10617
DOI: 10.1007/978-3-319-70353-4_46
OADOI: https://oadoi.org/10.1007/978-3-319-70353-4_46
Host publication editor: Blanc-Talon, Jacques
Penne, Rudi
Philips, Wilfried
Popescu, Dan
Scheunders, Paul
Conference: Advanced Concepts for Intelligent Vision Systems : 18th International Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Copyright information: © Springer International Publishing AG 2017. Published in this repository with the kind permission of the publisher.