Title
Cross-Database Micro-Expression Recognition: A Benchmark.
Abstract
Cross-database micro-expression recognition (CDMER) is one of recently emerging and interesting problem in micro-expression analysis. CDMER is more challenging than the conventional micro-expression recognition (MER), because the training and testing samples in CDMER come from different micro-expression databases, resulting in the inconsistency of the feature distributions between the training and testing sets. In this paper, we contribute to this topic from three aspects. First, we establish a CDMER experimental evaluation protocol aiming to allow the researchers to conveniently work on this topic and provide a standard platform for evaluating their proposed methods. Second, we conduct benchmark experiments by using NINE state-of-the-art domain adaptation (DA) methods and SIX popular spatiotemporal descriptors for respectively investigating CDMER problem from two different perspectives. Third, we propose a novel DA method called region selective transfer regression (RSTR) to deal with the CDMER task. Our RSTR takes advantage of one important cue for recognizing micro-expressions, i.e., the different contributions of the facial local regions in MER. The overall superior performance of RSTR demonstrates that taking into consideration the important cues benefiting MER, e.g., the facial local region information, contributes to develop effective DA methods for dealing with CDMER problem.
Year
DOI
Venue
2018
10.1145/3323873.3326590
ICMR '19: International Conference on Multimedia Retrieval Ottawa ON Canada June, 2019
Keywords
Field
DocType
cross-database micro-expression recognition, micro-expression recognition, domain adaptation, transfer learning, spatiotemporal descriptors
Facial expression recognition,Domain adaptation,Computer science,Transfer of learning,Artificial intelligence,Machine learning,Database
Journal
Volume
ISBN
Citations 
abs/1812.07742
978-1-4503-6765-3
1
PageRank 
References 
Authors
0.37
29
6
Name
Order
Citations
PageRank
Yuan Zong116217.39
Wenming Zheng2124080.70
Xiaopeng Hong337942.27
Chuangao Tang4284.25
Zhen Cui5146.66
Guoying Zhao63767166.92