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Less is more: Micro-expression recognition from video using apex frame.
- Source :
-
Signal Processing: Image Communication . Mar2018, Vol. 62, p82-92. 11p. - Publication Year :
- 2018
-
Abstract
- Despite recent interest and advances in facial micro-expression research, there is still plenty of room for improvement in terms of micro-expression recognition. Conventional feature extraction approaches for micro-expression video consider either the whole video sequence or a part of it, for representation. However, with the high-speed video capture of micro-expressions (100–200 fps), are all frames necessary to provide a sufficiently meaningful representation? Is the luxury of data a bane to accurate recognition? A novel proposition is presented in this paper, whereby we utilize only two images per video, namely, the apex frame and the onset frame. The apex frame of a video contains the highest intensity of expression changes among all frames, while the onset is the perfect choice of a reference frame with neutral expression. A new feature extractor, Bi-Weighted Oriented Optical Flow (Bi-WOOF) is proposed to encode essential expressiveness of the apex frame. We evaluated the proposed method on five micro-expression databases—CAS(ME) 2 , CASME II, SMIC-HS, SMIC-NIR and SMIC-VIS. Our experiments lend credence to our hypothesis, with our proposed technique achieving a state-of-the-art F1-score recognition performance of 0.61 and 0.62 in the high frame rate CASME II and SMIC-HS databases respectively. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09235965
- Volume :
- 62
- Database :
- Academic Search Index
- Journal :
- Signal Processing: Image Communication
- Publication Type :
- Academic Journal
- Accession number :
- 128044491
- Full Text :
- https://doi.org/10.1016/j.image.2017.11.006