Human emotion recognition system using optimally designed SVM with different facial feature extraction techniques

Authors:
G. U. Kharat;S. V. Dudul
Affiliations:
Research & Development, Anuradha Engineering College, Chikhli, Maharashtra, India;Applied Electronics Deptt., S.G.B. Amaravati University Amaravati, Maharashtra, India
Venue:
WSEAS Transactions on Computers
Year:
2008

Citing 15
Cited 2

Performance of optical flow techniques

International Journal of Computer Vision
Recognition of human facial expressions without feature extraction

ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow

IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Interpretation and Coding of Face Images Using Flexible Models

IEEE Transactions on Pattern Analysis and Machine Intelligence
Coding, Analysis, Interpretation, and Recognition of Facial Expressions

IEEE Transactions on Pattern Analysis and Machine Intelligence
Affective computing

Affective computing
Classifying Facial Actions

IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Motion Estimation in Model-Based Facial Image Coding

IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis and Synthesis of Facial Image Sequences Using Physical and Anatomical Models

IEEE Transactions on Pattern Analysis and Machine Intelligence
Example Based Image Analysis and Synthesis

Example Based Image Analysis and Synthesis
Subject independent facial expression recognition with robust face detection using a convolutional neural network

Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Toward Human-Level Machine Intelligence

ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Content-based image retrieval using wavelets

CEA'08 Proceedings of the 2nd WSEAS International Conference on Computer Engineering and Applications
Recognition of facial expressions and measurement of levels of interest from video

IEEE Transactions on Multimedia
Human expression recognition from motion using a radial basis function network architecture

IEEE Transactions on Neural Networks

Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge

Speech Communication
A novel fuzzy facial expression recognition system based on facial feature extraction from color face images

Engineering Applications of Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This research aims at developing "Humanoid Robots" that can carry out intellectual conversation with human beings. The first step in this direction is to recognize human emotions by a computer using neural network. In this paper all six universally recognized basic emotions namely angry, disgust, fear, happy, sad and surprise along with neutral one are recognized. Various feature extraction techniques such as Discrete Cosine Transform (DCT), Fast Fourier Transform (FFT), Singular Value Decomposition (SVD) are used to extract the useful features for emotion recognition from facial expressions. Support Vector Machine (SVM) is used for emotion recognition using the extracted facial features and the performance of various feature extraction technique is compared. Authors achieved 100% recognition accuracy on training dataset and 94.29% on cross validation dataset.