This document describes a proposed mobile application to help users network effectively at conferences. The main objectives are to identify other participants using augmented reality technologies like facial recognition and QR codes from a conference booklet. The application would allow users to search for participants by name or face, access profile information from integrated social networks, and contact participants through a personalized message board. The document outlines the technical design using iOS and various computer vision algorithms. It also discusses challenges, the current progress implementing facial detection and recognition, and the future timeline including usability testing.

1. By: Heng Wei Jian

2. 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

3. Motivation of work
In 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?

4. 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.

5. Approach
Platform: 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

6. Research Topics
Balance 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

7. Research Topics (cont)
Usefulness of the various user search tools for
identifying people.
 Textual Search
 Facial Search
 QR Search

8. 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

9. Technical Design
Tools:
 IOS4.0
 PHP remote server
 MySQL database
 OpenCV 2.0
 Facebook SDK
 ARPlus toolkit

10. Application Flowchart
Facebook
Login
Login
Account Normal
Settings Login
Conference
List
Textual Personal
Conference Message
Search
Details board
Participant Participant
Facial Search
List Details
QR Search

11. 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

12. General Approach
Grab image Augment
Facial Facial
from camera results on
Detection Recognition
frame screen

13. 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

14. Current Progress
iConference

15. Current Progress
Face 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

16. Current Progress
Face Recognition
1st 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

17. Current Progress
Face Recognition
2nd Method: Eigenfaces
-> Using PCA (Principal Component Analysis)
 Advantages
 Fast
 Uses less memory
 Disadvantages
 Build from scratch
 Proclaimed accuracy level: 60%

18. Current Progress
Image Pre-processing Techniques
Illumination
Face Alignment
Normalization
Original Rotated,Cropped,Resized HistogramEqualized

19. 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
Building the framework and foundation of the
WJ 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

20. DEMO

21. Screenshots (Face.com)

22. Screenshots (EigenFaces)

23. Screenshots
Original Cropped Greyscale and Equalized
resized