EMS: EXPRESSION BASED MOOD SHARING FOR SOCIAL NETWORKS

Md Munirul HaqueMohammad AdibuzzamanDepartment of Mathematics, Statistics, and Computer ScienceMarquette University

OUTLINE Motivation State of the art Classification of models FACS Drawbacks Comparison Open issues System Overview System Architecture Implementation

MOTIVATION Facebook has 500 million active users twitter has 190 million visitors per month Number of smart phone users has crossed 45

millions Many mood applications in FB

My Mood SpongeBob Mood The Mood Weather Report Name and Mood Analyzer Manual setting

STATE OF THE ART Active Appearance Model (AAM) Computer Expression Recognition Tool (CERT) Eigenface, Eigeneye, Eigenlips Artificial Neural Network (ANN) Relevance Vector Machine (RVM)

CLASSIFICATION

3D

Automatic Facial Expression Detection

Principal Component Analysis (PCA)

DimensionFocusClassification Technique

Artificial Neural Network (ANN)

Linear Discriminant Analysis (LDA) 2DPatientsAdultsNeonates

FACS

FACS

DRAWBACKS Reliability on clear frontal image Out-of-plane head rotation Right feature selection Fail to use temporal and dynamic information Considerable amount of manual interaction Noise, illumination, glass, facial hair, skin

color issues Computational cost Mobility Intensity Reliability.

COMPARISON

EIGENFACE, EIGENEYE, EIGENLIPS

Eigenfaces for the training image set

CHARACTERISTICS Real Time Mood to Social Media Location Aware Sharing Mood Aware Sharing

Mobility Resources of Behavioral Research Context Aware Event Manager

OPEN ISSUES Deception of Expression (suppression,

amplification, simulation) Difference in Cultural, Racial, and Sexual

Perception Intensity Dynamic Features

SYSTEM OVERVIEW

SYSTEM ARCHITECTURE

AXIS2

Apache Tomcat Container

Application Server

SOAP/Web Service Engine

Expression Detection Script

Server

WAMP

PHP Web Server

Browser/MobileHTTP Call

Client

FIG: Expression Detection Architecture

MATLAB

JAVA Library runs on MCR

MATLAB Builder JA

TRAINING DATABASE

WEB CLIENT

FUTURE WORK Build a Facebook application which will

capture the user image using device camera(webcam or mobile camera).

Feed that image to the MATLAB Script and get Expression detected.

Do a survey on the user response of the Facebook application

Increase accuracy Images- not present in the database Confusion matrix

CONCLUSION Most computational research requires the

extensive ability of MATLAB for different computations like image processing, forecasting and other areas.

Using web service to run a MATLAB script will help do research on Computational sciences research.

Q/A Any question?? Comments Suggestion