From Macro to Micro Expression Recognition: Deep Learning on Small Datasets Using Transfer Learning

Min Peng · Zhan Wu · Zhihao Zhang · Tong Chen

156 citations0/0 files storedInternational Conference on Automatic Face and Gesture Recognition

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Emotion and Mood Recognition Face recognition and analysis Face and Expression Recognition

Abstract

This paper presents the methods used in our submission to 2018 Facial Micro-Expression Grand Challenge (MEGC). The object of the challenge is to recognize micro-expression in two provided databases, including holdout-database recognition and composite database recognition. Considering the small size of the databases, we follow a rout of transfer learning to implement convolutional neural network to recognize the micro-expression. ResNet10 pre-trained on ImageNet dataset was fine-tuned on macro-expression datasets with large size and then on the provided micro-expression datasets. Experimental results show that the method can achieve weighted average recall (WAR) of 0.561 and unweighted average recall (UAR) of 0.389 in Holdout-database Evaluation Task, and F1 Score of 0.64 in Composite Database Evaluation Task, which are much higher than what baseline methods (LBP-TOP, HOOF, HOG3D) can achieve.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 156 citations exist upstream.

References

2010The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression 2014CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation 2016SAMM: A Spontaneous Micro-Facial Movement Dataset 2015A Main Directional Mean Optical Flow Feature for Spontaneous Micro-Expression Recognition 2008Reading Between the Lies 2017Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods 2010The MUG facial expression database 2016Microexpression Identification and Categorization Using a Facial Dynamics Map

Cited by

2019Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural Networks 2020Dynamic Micro-Expression Recognition Using Knowledge Distillation 2019Recognizing Facial Expressions Using a Shallow Convolutional Neural Network 2022ME-PLAN: A deep prototypical learning with local attention network for dynamic micro-expression recognition 2020Spatiotemporal Convolutional Neural Network with Convolutional Block Attention Module for Micro-Expression Recognition

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.