MERCoL: video-based facial micro-expression recognition via bimodal contrastive learning
by Yanxin Song; Pengyu Wang; Hao Sun; Lei Chen; Xianye Ben
International Journal of Computer Applications in Technology (IJCAT), Vol. 71, No. 4, 2023

Abstract: Micro-expressions are brief, subtle, involuntary facial gestures revealing genuine mental activity, with numerous real-world applications. Owing to their transient nature, low intensity, and capture difficulty, many existing recognition algorithms based on handcrafted features and deep learning methods lack accuracy. We propose a micro-expression recognition framework called MERCoL, which utilises bimodal contrastive learning to extract common and distinctive features from limited dataset samples. The network comprises three modules: bimodal feature extraction, bimodal contrastive learning fusion, and classification. First, micro-expression sequences are divided into RGB and optical flow sequences, with a contrastive learning-based loss function for learning common bimodal features. Second, bimodal features are then fused and labelled data is used to optimise the network for distinctive feature learning. At last, experiments on CASME II, SAMM, and MMEW datasets demonstrate our algorithm's superiority compared to state-of-the-art methods.

Online publication date: Wed, 19-Jul-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com