scispace - formally typeset
Journal ArticleDOI

Facial expression recognition - A real time approach

TLDR
In this paper, a method for facial expression recognition is proposed that finds an optimal hyperplane to distinguish different facial expressions with an accuracy of 98.5%.
Abstract
Face localization, feature extraction, and modeling are the major issues in automatic facial expression recognition. In this paper, a method for facial expression recognition is proposed. A face is located by extracting the head contour points using the motion information. A rectangular bounding box is fitted for the face region using those extracted contour points. Among the facial features, eyes are the most prominent features used for determining the size of a face. Hence eyes are located and the visual features of a face are extracted based on the locations of eyes. The visual features are modeled using support vector machine (SVM) for facial expression recognition. The SVM finds an optimal hyperplane to distinguish different facial expressions with an accuracy of 98.5%.

read more

Citations
More filters
Journal ArticleDOI

Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications

TL;DR: A new taxonomy of automatic RGB, 3D, thermal and multimodal facial expression analysis is defined, encompassing all steps from face detection to facial expression recognition, and described and classify the state of the art methods accordingly.
Posted Content

Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-related Applications

TL;DR: Facial expressions are an important way through which humans interact socially as mentioned in this paper, and much research is needed about the way they relate to human affect, and a taxonomy of facial expression analysis methods can be found in this paper.
Journal ArticleDOI

EOG-based Human-Computer Interface system development

TL;DR: The preliminary results revealed more than 90% accuracy rate for examining the eye-movement that may become a new useful human-machine user interface in the near future.
Journal ArticleDOI

Ensemble of Deep Neural Networks with Probability-Based Fusion for Facial Expression Recognition

TL;DR: An ensemble of convolutional neural networks method with probability-based fusion for facial expression recognition, where the architecture of CNN was adapted by using the Convolutional rectified linear layer as the first layer and multiple hidden maxout layers.
Journal ArticleDOI

Breast mass classification based on cytological patterns using RBFNN and SVM

TL;DR: It is demonstrated that RBFNN outperformed the polynomial kernel of SVM for correctly classifying the tumors and the results were compared to convey and compare the qualities of the classifiers.
References
More filters
Book

Neural Networks: A Comprehensive Foundation

Simon Haykin
TL;DR: Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.

Statistical learning theory

TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Journal ArticleDOI

A Tutorial on Support Vector Machines for Pattern Recognition

TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Journal ArticleDOI

Pfinder: real-time tracking of the human body

TL;DR: Pfinder is a real-time system for tracking people and interpreting their behavior that uses a multiclass statistical model of color and shape to obtain a 2D representation of head and hands in a wide range of viewing conditions.
Journal ArticleDOI

Neural network-based face detection

TL;DR: A neural network-based upright frontal face detection system that arbitrates between multiple networks to improve performance over a single network, and a straightforward procedure for aligning positive face examples for training.
Related Papers (5)