Citation

Liong, Sze Teng and See, John and Wong, Kok Sheik and Le Ngo, Anh Cat and Oh, Yee Hui and Phan, Raphael Chung Wei (2016) Automatic apex frame spotting in micro-expression database. In: 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR). IEEE, pp. 665-669. ISBN 978-1-4799-6100-9

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Abstract

Micro-expression usually occurs at high-stakes situations and may provide useful information in the field of behavioral psychology for better interpretion and analysis. Unfortunately, it is technically challenging to detect and recognize micro-expressions due to its brief duration and the subtle facial distortions. Apex frame, which is the instant indicating the most expressive emotional state in a video, is effective to classify the emotion in that particular frame. In this work, we present a novel method to spot the apex frame of a spontaneous micro-expression video sequence. A binary search approach is employed to locate the index of the frame in which the peak facial changes occur. Features from specific facial regions are extracted to better represent and describe the expression details. The defined facial regions are selected based on the action unit and landmark coordinates of the subject, in which case these processes are automated. We consider three distinct feature descriptors to evaluate the reliability of the proposed approach. Improvements of at least 20% are achieved when compared to the baselines.

Item Type:	Book Section
Uncontrolled Keywords:	Feature extraction, Face, Strain, Mouth, Databases, Face recognition, Eyebrows
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions:	Faculty of Computing and Informatics (FCI) Faculty of Engineering (FOE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	07 Dec 2017 12:18
Last Modified:	07 Dec 2017 12:18
URII:	http://shdl.mmu.edu.my/id/eprint/6568

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