Facial Expression Recognition Using Facial Graph
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- 作者：Sina Mohseni (17)
Niloofar Zarei (18)
Ehsan Miandji (19)
Gholamreza Ardeshir (17)
17. Faculty of Electrical Engineering ; Noshirvani University of Technology ; Babol ; Iran
18. Faculty of Electrical Engineering ; Amirkabir University of Technology ; Tehran ; Iran
19. The Visual Computing Laboratory ; Link枚ping University ; Norrk枚ping ; Sweden - 关键词：Facial expression analysis ; Facial feature points ; Facial graph ; Support vector machine ; Adaboost classifier
- 刊名：Lecture Notes in Computer Science
- 出版年：2015
- 出版时间：2015
- 年：2015
- 卷：8912
- 期：1
- 页码：58-66
- 全文大小：650 KB
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- 丛书名：978-3-319-13736-0
- 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
Automatic analysis of human facial expression is one of the challenging problems in machine vision systems. It has many applications in human-computer interactions, social robots, deceit detection, interactive video and behavior monitoring. In this paper, we developed a new method for automatic facial expression recognition based on verifying movable facial elements and tracking nodes in sequential frames. The algorithm plots a face model graph in each frame and extracts features by measuring the ratio of the facial graph sides. Seven facial expressions, including neutral pose are being classified in this study using support vector machine and other classifiers on JAFFE databases. The approach does not rely on action units, and therefore eliminates errors which are otherwise propagated to the final result due to incorrect initial identification of action units. Experimental results show that analyzing facial movements gives accurate and efficient information in order to identify different facial expressions.