scholarly journals Facial Expression Recognition Using Digitalised Facial Features Based on Active Shape Model

2016 ◽  
Author(s):  
Nan Sun ◽  
Zheng Chen ◽  
Richard Day
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Active Shape Model ◽  
Facial Features ◽  
Expression Recognition ◽  
Shape Model ◽  
Active Shape

Weight Calculation Based Image Recognition

2013 ◽  
Vol 303-306 ◽  
pp. 1577-1580
Author(s):  
Yi Fan Yuan ◽  
Jun Ping Du ◽  
Jun Zhou ◽  
Cheng Lu ◽  
Er Wei Bai ◽  
...  
Keyword(s):  
Facial Expression ◽  
Image Recognition ◽  
Expression Vector ◽  
Active Shape Model ◽  
Facial Features ◽  
Expression Recognition ◽  
Shape Model ◽  
Static Image ◽  
Weight Calculation ◽  
Universal Expression

The method to recognize facial expression in images quickly has been widely applied in many areas, but there is no way to take into account the accuracy and speed of recognition. This paper presents a method based on the weight calculation for fast expression recognition. It first calculates facial features based on active shape model, and then matches the features to the standard expression vector got by large number of image training and recognizes the expression in the static image. The experiments show that the system can provide fast, universal expression recognizing function under the premise of guaranteeing an ideal accuracy.

scholarly journals Facial Expression Analysis by Machine Learning

2010 ◽  
pp. 239-258
Author(s):  
Siu-Yeung Cho ◽  
Teik-Toe Teoh ◽  
Yok-Yen Nguwi
Keyword(s):  
Feature Selection ◽  
Facial Expression ◽  
Real Time ◽  
Facial Expression Recognition ◽  
Classification Performance ◽  
Difficult Problem ◽  
Facial Features ◽  
Expression Recognition ◽  
Real Time Processing ◽  
Good Classification Performance

Facial expression recognition is a challenging task. A facial expression is formed by contracting or relaxing different facial muscles on human face that results in temporally deformed facial features like wide-open mouth, raising eyebrows or etc. The challenges of such system have to address with some issues. For instances, lighting condition is a very difficult problem to constraint and regulate. On the other hand, real-time processing is also a challenging problem since there are so many facial features to be extracted and processed and sometimes, conventional classifiers are not even effective in handling those features and produce good classification performance. This chapter discusses the issues on how the advanced feature selection techniques together with good classifiers can play a vital important role of real-time facial expression recognition. Several feature selection methods and classifiers are discussed and their evaluations for real-time facial expression recognition are presented in this chapter. The content of this chapter is a way to open-up a discussion about building a real-time system to read and respond to the emotions of people from facial expressions.

Facial Features Extraction based on Active Shape Model

2013 ◽  
Vol 8 (6) ◽  
Author(s):  
Qihui Wang ◽  
Lijun Xie ◽  
Bo Zhu ◽  
Tingjun Yang ◽  
Yao Zheng
Keyword(s):  
Features Extraction ◽  
Active Shape Model ◽  
Facial Features ◽  
Shape Model ◽  
Active Shape
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