Method of Detecting Concentration on Cellular Phone Call from Facial Expression Change by Image Processing

2006 ◽  
Author(s):  
K. Takahashi ◽  
K. Yamada ◽  
T. Nakano ◽  
Shin Yamamoto
Keyword(s):  
Image Processing ◽  
Facial Expression ◽  
Cellular Phone ◽  
Phone Call ◽  
Expression Change

Detecting Facial Expression by Concentration on Cellular Phone Call

2005 ◽  
Vol 125 (12) ◽  
pp. 1812-1817
Author(s):  
Kenichi Takahashi ◽  
Osami Yamamoto ◽  
Tomoaki Nakano ◽  
Shin Yamamoto
Keyword(s):  
Facial Expression ◽  
Cellular Phone ◽  
Phone Call

RECOGNITION OF FACIAL EXPRESSION BY IMAGE PROCESSING AND RADIAL BASIS FUNCTION NETWORK

2016 ◽  
Author(s):  
Olímpio Murilo Capeli ◽  
Euvaldo Ferreira Cabral Junior ◽  
Sadao Isotani ◽  
Antonio Roberto Pereira Leite de Albuquerque
Keyword(s):  
Image Processing ◽  
Facial Expression ◽  
Radial Basis Function ◽  
Basis Function ◽  
Radial Basis Function Network ◽  
Radial Basis ◽  
Function Network

A Robotic Facial Expression Recognition System Using Real-Time Vision System

2008 ◽  
Vol 381-382 ◽  
pp. 375-378
Author(s):  
K.T. Song ◽  
M.J. Han ◽  
F.Y. Chang ◽  
S.H. Chang
Keyword(s):  
Image Processing ◽  
Facial Expression ◽  
Real Time ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Vision System ◽  
Recognition System ◽  
Expression Recognition ◽  
On Line ◽  
Processing Platform

The capability of recognizing human facial expression plays an important role in advanced human-robot interaction development. Through recognizing facial expressions, a robot can interact with a user in a more natural and friendly manner. In this paper, we proposed a facial expression recognition system based on an embedded image processing platform to classify different facial expressions on-line in real time. A low-cost embedded vision system has been designed and realized for robotic applications using a CMOS image sensor and digital signal processor (DSP). The current design acquires thirty 640x480 image frames per second (30 fps). The proposed emotion recognition algorithm has been successfully implemented on the real-time vision system. Experimental results on a pet robot show that the robot can interact with a person in a responding manner. The developed image processing platform is effective for accelerating the recognition speed to 25 recognitions per second with an average on-line recognition rate of 74.4% for five facial expressions.

Research of Feature Extraction Method on Facial Expression Change

2011 ◽  
Vol 211-212 ◽  
pp. 813-817 ◽  
Author(s):  
Jin Qing Liu ◽  
Qun Zhen Fan
Keyword(s):  
Feature Extraction ◽  
Wavelet Transform ◽  
Facial Expression ◽  
Extraction Method ◽  
Dimensional Space ◽  
Recognition Rate ◽  
Low Frequency ◽  
Expression Change ◽  
Feature Extraction Method ◽  
Low Dimensional

In this paper, the purpose is to find a method that can be more suited to facial expression change and also improve the recognition rate. The proposed system contains three parts, wavelet transform, Fisher linear discriminant method feature extraction and face classification. The basic idea of the proposed method is that first extract the low-frequency components through wavelet transform, then the low-frequency images mapped into a low-dimensional space by PCA transform, and finally the utilization of LDA feature extraction method in low-dimensional space. The algorithms were tested on ORL and Yale face database, respectively. Experimental results shows that the proposed method not only improve the recognition rate, but also improve the recognition speed. This method can effectively overcome the impact of expression changes on face recognition, and play a certain role in inhibition of expression.

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