Micro-Expression Recognition Using Robust Principal Component Analysis and Local Spatiotemporal Directional Features

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• 作者：Su-Jing Wang (16) (19)
  Wen-Jing Yan (16) (17)
  Guoying Zhao (18)
  Xiaolan Fu (16)
  Chun-Guang Zhou (19)
  
  16. State Key Lab of Brain and Cognitive Science ; Institute of Psychology ; Chinese Academy of Sciences ; Beijing ; 100101 ; China
  19. College of Computer Science and Technology ; Jilin University ; Changchun ; 130012 ; China
  17. College of Teacher Education ; Wenzhou University ; Wenzhou ; China
  18. Center for Machine Vision Research ; University of Oulu ; Oulu ; Finland
  
• 关键词：Micro ; expression recognition ; Sparse representation ; Dynamic features ; Local binary pattern ; Subtle motion extraction
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：8925
• 期：1
• 页码：325-338
• 全文大小：631 KB
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• 作者单位：Computer Vision - ECCV 2014 Workshops
• 丛书名：978-3-319-16177-8
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

One of important cues of deception detection is micro-expression. It has three characteristics: short duration, low intensity and usually local movements. These characteristics imply that micro-expression is sparse. In this paper, we use the sparse part of Robust PCA (RPCA) to extract the subtle motion information of micro-expression. The local texture features of the information are extracted by Local Spatiotemporal Directional Features (LSTD). In order to extract more effective local features, 16 Regions of Interest (ROIs) are assigned based on the Facial Action Coding System (FACS). The experimental results on two micro-expression databases show the proposed method gain better performance. Moreover, the proposed method may further be used to extract other subtle motion information (such as lip-reading, the human pulse, and micro-gesture etc.) from video.