Learning a Target Sample Re-Generator for Cross-Database Micro-Expression Recognition

Abstract

In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.

To appear at ACM Multimedia 2017

References in corpus (2)

• Very Deep Convolutional Networks for Large-Scale Image Recognition
• Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods

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• A Deeper Look at Facial Expression Dataset Bias
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• Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning
• Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition
• Cross-database non-frontal facial expression recognition based on transductive deep transfer learning
• AU-Guided Unsupervised Domain Adaptive Facial Expression Recognition
• Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition
• Cross-Database Micro-Expression Recognition: A Benchmark
• Seeking Salient Facial Regions for Cross-Database Micro-Expression Recognition
• Region attention and graph embedding network for occlusion objective class-based micro-expression recognition