Sunday, August 28, 2011

Ultra low cost computer from Raspberry Pi Foundation

Raspberry Pi Foundation is set to launch its USD25 (Approx. RM75) ARM-based single-board computer by end of this year. It is just the size of a credit card. Plug in monitor and keyboard via HDMI and USB connection, respective, and voila!

* 700MHz ARM11
* 128MB or 256MB of SDRAM
* OpenGL ES 2.0
* 1080p30 H.264 high-profile decode
* Composite and HDMI video output
* USB 2.0
* SD/MMC/SDIO memory card slot
* General-purpose I/O
* Optional integrated 2-port USB hub and 10/100 Ethernet controller
* Open software (Ubuntu, Iceweasel, KOffice, Python)

The following video shows the prototype runs Quake 3 game:



Raspberry Pi $25 Model
Raspberry Pi $25 Model

Thursday, August 25, 2011

Postgraduate Seminar at UTAR KL Campus

Dear All,

We wish to inform that the Postgraduate Seminar for proposal defence
is scheduled as follows:-

Speaker: Chai Yung Joon
Date: 26/08/2011
Time: 10:00am-10:45am
Venue: 5A meeting room, SA Block, FES, UTAR KL Campus.
Title: Object Removal on Video Surveillance System
Abstract:
Nowadays, thievery is a common crime in the world. It can happen
anytime, from morning to night and anywhere from housing area to
public places. It makes the people feel so unsafe when they cannot
look after their valuable items such as travelling, out of home and so
on. Therefore, surveillance systems are employed at many places to
reduce the chance of the thievery happen. But normally be surveillance
systems need to be monitored by single operator. When human explore to
this kind of work for long time, they will be tire and easy make
mistake when then probability to miss dangerous situation will
increase. Thus, a semiautomatic surveillance system can be used to
help operator to detect thievery crime by giving some intelligences to
the system.
The major problem of surveillance systems is they normally only can
record the video and some of them able to detect there have something
moving in the scene. But the systems lack of the ability to detect and
track interest objects and human in video scene. When human and
objects can be tracked then further analysis can be done more
efficiently. Besides this, the systems also lack of the ability to
determine the person that take away the interested object. If the
system cannot give alert immediately, there will be a chance that the
thief can escape from scene.
This proposed system aims to address the above issues, which included
detect all interested objects in the scene at beginning of the video,
detect and track human in scene, and define the relationship between
human and interested objects in term of remove the object and occlude
the object. Besides this, the system aimed to run in 24 hours per day
which met the requirement of a standard surveillance system.
The proposed system can be divided to three modules, which are
foreground detection, human tracking and object removal detection. In
the scene, there will be a lot of interested objects and uninterested
objects. Foreground detection module will extract interested
foreground objects from background when the video start. After the
interested object detection in first module, all the interested
objects will be keeping tracked to use in object removal module. The
human tracking module will keep track on human who go into the video
scene until they are out of the scene. In object removal module, when
someone takes the interested objects in scene, the event should be
detected and the system able to tell which person took the objects.
This module also needs detect someone only occludes an interested
object but he/ she does not take away the object.
In conclusion, the proposed system aimed to detect and give alert when
people trying steal valuable items. It can help improve security level
in our society and lead us to have a better harmony environment.

Speaker: Kee Hong Sheng
Date: 26/08/2011
Time: 10:45am-11:30am
Venue: 5A meeting room, SA Block, FES, UTAR KL Campus.
Title: Unattended Object Detection Base on Video Surveillance Camera
Abstract
Nowadays, the awareness of terrorist attack prevention are becoming a
concerning issue in Malaysia. Many countries are also implementing
various security measurements to prevent terrorist attack. Setting up
surveillance cameras in strategic areas is one of the latest effective
measurements employed to detect such activities, where there are
surveillance cameras already set up everywhere, for instance,
government offices, airport terminals, car parks, staircases.
However, in order to monitor all the video scenes captured by the
surveillance cameras, it requires considerable human resource and
time. This project choose to detect unattended object, the main reason
is in a scene of surveillance cameras, the unattended object stay
static mostly all the time, and it's very hard to draw the attention
of the security personnel.
Hence, this project attempts to develop a system that is able to
automate the detection of possible occurrence of unattended object,
and hence alert the security personnel to pay attention to the
detected event, eventually some adequate measures can be carry out, to
minimize the probability of unpleasant incident to happen.
To develop a system that is able to widely implement, the system must
not required high resolution video image, where currently most of the
surveillance camera are low resolution or even maybe only able to
capture greyscale video. Processing high resolution video image will
also require higher processing power, or the efficiency of the system
will be affected. Hence, implement high resolution video image will
increase the implementing cost by increasing camera cost and also
processing unit cost.
The project proposes a human-object interaction analysis system that
detects human-object interaction, and the detected human-object
interaction will be monitored in the system. If the human-object
distance is too far, after a period of time, the object will be
considered as unattended object. The unattended object will be marks
up by the system, and the object owner will also be keep tracked.
In this project, the system dealing with human and object in a video
sequence, in most of the time, human and object will occlude each
other. The system scope will cover until object partially occlusion,
where fully occlusion include more uncertainty.
The Seminar is opened to public. All are welcome to attend the Seminar.

Thursday, August 18, 2011

Research Assistants Needed


RESEARCH ASSISTANT (RA)

Number of Vacancies: 2
Available at 
Faculty of Engineering & Science, Universiti Tunku Abdul Rahman (UTAR)
KL Campus, Setapak, Kuala Lumpur

Project Title
Computer vision algorithm and software development for the application of urban traffic monitoring.

Project Leader
Associate Professor Dr. Tay Yong Haur (tayyh@utar.edu.my),
Department of Internet Engineering and Computer Science,
Faculty of Engineering and Science (FES), UTAR KL Campus.

Objective
To involve in the software development and continuous algorithm improvement of a computer vision-based software product for urban traffic monitoring.

Scope of Work

•          To evaluate the performance of the existing algorithm;
•          To recommend improvement on the existing algorithm;
•          To develop and evaluate an improved computer vision algorithm;
•          To integrate the improved algorithm into the software package;
•          To perform software development to enhance the overall software package
•          To work closely with research engineers from the industry.

Job Description

•          Remuneration of RM2000-2500 per month for 12 months.
•          The RA must help the project leader in all works associated with the research.
•          The RA must work closely with the sponsored industry partner to complete the research project.
•          The RA may register for Master Degree by research program (M. EngSc) with UTAR.

Requirements

•          Passionate in computer programming, especially in C/C++/C#
•          Strong interest and/or has working experience in image processing / pattern recognition project / GPU
•          Good English written and verbal communication
•          Good analytical skills
•          Self-motivated, requires minimal supervision, resourceful and willing to learn.
•          Available to start working preferably on 1 October 2011.

If you are interested in the RA position advertised above, please email your CV directly to Dr. Tay Yong Haur (tayyh@utar.edu.my) as soon as possible. Feel free to write to Dr Tay for any further inquiry of the project.

Only short-listed candidates will be called for interview.

Friday, August 5, 2011

Biometric School 2012 (Winter Edition) -- annoucement


 

Please open the online version of this message if the HTML is not correctly displayed.

 

(approval pending)      

Biometric School 2012 (Winter Edition)

Permai Rainforest Resort, Kuching, Sarawak, Malaysia

9-13 January 2012

www.biometricschool.org

Just announced : Biometric School 2012 programme

Register now to hear from top international speakers on the latest developments in biometrics technology.

View the full programme.

Topics include :

  • Fundamentals of fingerprint recognition, Prof. Davide Maltoni (Italy)
  • Touchless fingerprint recognition & Biometrics and privacy protection, Prof. Jaihie Kim (Korea)
  • Iris recognition, Prof. Tieniu Tan (China)
  • Face recognition, Dr. Simon Prince (UK)
  • Linear and advanced classifier design for biometric systems, Prof. Kar-ann Toh (Korea)
  • Fusion strategies and template security in biometric systems, Dr. Karthik Nandakumar (Singapore)
  • Advanced techniques for multimodal biometric fusion : quality, cohort and client-dependent strategies, Dr. Norman Poh (UK)
  • Biometric-key computation, Dr. Andrew Teoh (Korea)

 Remember to book by 31 October 2011 to get the best rate.

Sponsors
Planet Biometrics United Technology

To sponsor the event, please contact us

 For any enquiry, please visit www.biometricschool.org or drop us an email at info@biometricschool.org


Norman
--------------------------------------------------------------------------------------------------------
PS: "normanpoh@gmail.com" will no longer be used. Please use "n.poh@surrey.ac.uk" instead.
--------------------------------------------------------------------------------------------------------

Dr Norman Poh
Research Fellow
CVSSP,
Department of Electronic Engineering
University of Surrey
Guildford, U.K.
http://www.ee.surrey.ac.uk/Personal/Norman.Poh

Attending the Stanford University's AI course

Missing your Artificial Intelligence class? ;) Register yourself to attend the Introduction to Artificial Intelligence course offered by Stanford University, together with the students in Stanford University, for free!

The course will be taught by Prof. Sebastian Thrun, and Peter Norvig, the co-author of the popular AI book, AI: A Modern Approach.

The course will run from October to December 2011. You will be expected to watch the same lectures, complete the same assignments, and take the same examinations as the Stanford's students who sign up for the course. You will receive grades for your assignments and examinations, and will get certificates created by the professors if you manage to complete the course!

Below is the schedule:

DateContentHomework & Exams
Week of Oct 3Overview of AI, SearchAssignment 1 due Oct 9
Week of Oct 10Statistics, Uncertainty, and Bayes networksAssignment 2 due Oct 16
Week of Oct 17Machine LearningAssignment 3 due Oct 23
Week of Oct 24Hidden Markov models and Bayes filtersAssignment 4 due Oct 30
Week of Oct 31Markov Decision Porcesses and and Reinforcement LearningAssignment 5 due Nov 7
Week of Nov 7Adversarial planning (games) and belief space planning (POMDPs)MIDTERM EXAM due Nov 13
Week of Nov 14Logic and Logical Problem SolvingAssignment 6 due Nov 20
Week of Nov 21Image Processing and Computer VisionAssignment 7 due Nov 27
Week of Nov 28Robotics and robot motion planningAssignment 8 due Dec 4
Week of Dec 5Natural Language Processing and Information Retrieval
Week of Dec 12FINAL EXAM due Dec 18

If you are interested, please register at http://www.ai-class.com/ before 10 Sept 2011.

Watch the introductory videos here:





Talk by Prof Brian A. Barsky, UC Berkeley

You are cordially welcome to attend the talk by Prof Brian A. Barsky on various aspects of computer science teaching and research at University California Berkeley.

Date: Monday, 8th August 2011
Time: 1:00PM ~ 1:45PM
Venue: IDK5, Kampar Campus,Universiti Tunku Abdul Rahman

Speaker: Prof. Brian A. Barsky
Brian A. Barsky is Professor of Computer Science and Affiliate Professor of Optometry and Vision Science at the UC Berkeley. His research interests include computer aided geometric design and modeling, interactive three-dimensional computer graphics, visualization in
scientific computing, computer aided cornea modeling and visualization, medical imaging, and virtual environments for surgical simulation.

Abstract:
In his talk, Prof. Barsky will share some of his insights and experience as a senior academic staff on various aspects of computer science teaching and research at UC Berkeley, which has been consistently one of the top ranked computer science schools in the United States and globally. UC Berkeley staff and alumni have garnered a total of 15 Turing awards (which is considered to be the "Nobel Prize" of computing) since its inception. It has been the source of common computer science products such as Berkeley Unix, relational databases, RAID (Redundant Arrays of Inexpensive Disks), Reduced Instruction Set Computing (RISC) and Simulation Program with
Integrated Circuit Emphasis (SPICE).

Attending the Stanford University's AI course

Missing your Artificial Intelligence class? ;) Register yourself to attend the Introduction to Artificial Intelligence course offered by Stanford University, together with the students in Stanford University, for free!

The course will be taught by Prof. Sebastian Thrun, and Peter Norvig, the co-author of the popular AI book, AI: A Modern Approach.

The course will run from October to December 2011. You will be expected to watch the same lectures, complete the same assignments, and take the same examinations as the Stanford's students who sign up for the course. You will receive grades for your assignments and examinations, and will get certificates created by the professors if you manage to complete the course!

Below is the schedule:

DateContentHomework & Exams
Week of Oct 3Overview of AI, SearchAssignment 1 due Oct 9
Week of Oct 10Statistics, Uncertainty, and Bayes networksAssignment 2 due Oct 16
Week of Oct 17Machine LearningAssignment 3 due Oct 23
Week of Oct 24Hidden Markov models and Bayes filtersAssignment 4 due Oct 30
Week of Oct 31Markov Decision Porcesses and and Reinforcement LearningAssignment 5 due Nov 7
Week of Nov 7Adversarial planning (games) and belief space planning (POMDPs)MIDTERM EXAM due Nov 13
Week of Nov 14Logic and Logical Problem SolvingAssignment 6 due Nov 20
Week of Nov 21Image Processing and Computer VisionAssignment 7 due Nov 27
Week of Nov 28Robotics and robot motion planningAssignment 8 due Dec 4
Week of Dec 5Natural Language Processing and Information Retrieval
Week of Dec 12 FINAL EXAM due Dec 18

If you are interested, please register at http://www.ai-class.com/ before 10 Sept 2011.

Watch the introductory videos here:






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