Journal
OPTIK
Volume 126, Issue 23, Pages 4446-4451Publisher
ELSEVIER GMBH
DOI: 10.1016/j.ijleo.2015.08.167
Keywords
Micro-expressions; Recognition rate; CBP-TOP; ELM
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Funding
- National Natural Science Foundation of China [60302018]
- Tianjin Sci-tech Planning Projects of China [14RCJFJX00845]
- Natural Science Foundation of Hebei Province of China [F2015202239]
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Micro-expressions are short, involuntary facial expressions with revealing suppressed effect that people try to conceal. Detecting and recognizing micro-expressions have potential applications in clinical and national security fields. Centralized Binary Patterns from Three Orthogonal Panels (CBP-TOP) is a novel approach that can efficiently extract the micro-expression information in spatial and temporal domains. In this method, the micro-expression image sequences are initially preprocessed that includes face detection, interception, size normalization, and micro-expression detection. Then, the features of the human face are extracted from the blocks of images, using CBP-TOP operator. Finally, extreme learning machine (ELM) is used to recognize micro-expressions. The experimental results show that this method can extract motion features and dynamic texture information in micro-expression sequences more efficiently and has greater improvement in micro-expressions recognition rate than the traditional recognition methods. (C) 2015 Elsevier GmbH. All rights reserved.
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