By: Heng Wei Jian

Motivation of work Main objective at conference -> Network with other

participants

Golden opportunity that is often wasted

Build a new mobile platform that facilitates this process

Finding and presenting essential information to the user using augmented reality technologies

Motivation of workIn a conference:

Who should I talk to?

Who is that guy over there? He seems familiar.

How do I find out more about him?

How do I get an opportunity to talk to him?

How do I approach him?

Project Objectives

To create a mobile application that enables users to network effectively with other participants in a conference

Evaluate the usefulness of the system.

ApproachPlatform: iPhone 4

Main Features:(Who to talk to?) Real-time mobile Facial Search Conference booklet with QRCodes

(How to find out more about him?) Facebook integration

(How to contact him?) Real-time personalized message board

Research TopicsBalance between privacy concerns and ease of use

• Find out best possible way to gather information about participants in a conference without intruding their privacy but requiring minimal user input

• Can make use of existing social networks to get participants information but needs to be appropriate in a conference context

Research Topics (cont)Usefulness of the various user search tools for identifying people.

Textual Search

Facial Search

QR Search

Research Topics (cont)Effectiveness of mobile tool for conference networking purposes

Evaluation of system Ease of use

Error frequency

Interface design

Task suitability

Satisfaction

Privacy concerns

Technical DesignTools:

IOS4.0

PHP remote server

MySQL database

OpenCV 2.0

Facebook SDK

ARPlus toolkit

Application Flowchart

Login

Normal Login

FacebookLogin

Conference List

QR Search

Facial Search

Textual Search

Participant List

Conference Details

Participant Details

Personal Message

board

Account Settings

Core Feature: Facial Search Allows user to easily identify other participants in the

conference using facial detection and facial recognition technologies

Non-intrusive and appropriate in conference context

Training images can be obtained from social networks to relieve user manual input

Results augmented on screen

General Approach

Grab image from camera

frame

Facial Detection

Facial Recognition

Augment results on

screen

Challenges Running speed on Mobile Devices Most algorithms require fast CPU speed and high

memory

Accuracy Accuracy is heavily dependent on pose and illumination

Obtaining Training Images Get sufficient quality training images without heavy user

input

Capturing moving images

Distance factor

Current Progress

iConference

Current ProgressFace Detection

OpenCV

Implements Viola-Jones object detection framework

Makes use of Haar Classifier to describe and find general facial features

Accuracy level for frontal view : 95%

Already tested on the phone – average of 1 to 2s

Current ProgressFace Recognition1st Method: Face.com

->3rd party web-based recognition tool

Advantages: Easy to use

Accuracy level: 70%

Disadvantages: Not open source

Huge overhead to post image to web to get results

Slow

Current ProgressFace Recognition2nd Method: Eigenfaces

-> Using PCA (Principal Component Analysis)

Advantages Fast

Uses less memory

Disadvantages Build from scratch

Proclaimed accuracy level: 60%

Current ProgressImage Pre-processing Techniques

Original Rotated,Cropped,Resized HistogramEqualized

Face AlignmentIllumination

Normalization

Timeline:Mar Apr May Jun Jul Aug Sep Oct Nov

1 Research and Implementation

V Research on QR's current implementation

V Implement QR algorithm in ObjectiveC

V Implement QR tracking in the booklet

WJ System Design and Modelling

WJ

Building the framework and foundation of the

application

2 Integration and Iteration

V Ensure Accuracy and Tweaks to QR tracking

WJ Adding extra features to Application

V & WJ Modifications to application based on tests

3 Usability and Thesis

V & WJ Carry out usability tests at conferences

V & WJ Thesis and Technical Paper

DEMO

Screenshots (Face.com)

Screenshots (EigenFaces)

Screenshots

Original Cropped Greyscale and resized

Equalized