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.
|
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 | |
| 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 :
Remember to book by 31 October 2011 to get the best rate. | |
| Sponsors To sponsor the event, please contact us | |
| For any enquiry, please visit www.biometricschool.org or drop us an email at info@biometricschool.org | |
| Date | Content | Homework & Exams |
| Week of Oct 3 | Overview of AI, Search | Assignment 1 due Oct 9 |
| Week of Oct 10 | Statistics, Uncertainty, and Bayes networks | Assignment 2 due Oct 16 |
| Week of Oct 17 | Machine Learning | Assignment 3 due Oct 23 |
| Week of Oct 24 | Hidden Markov models and Bayes filters | Assignment 4 due Oct 30 |
| Week of Oct 31 | Markov Decision Porcesses and and Reinforcement Learning | Assignment 5 due Nov 7 |
| Week of Nov 7 | Adversarial planning (games) and belief space planning (POMDPs) | MIDTERM EXAM due Nov 13 |
| Week of Nov 14 | Logic and Logical Problem Solving | Assignment 6 due Nov 20 |
| Week of Nov 21 | Image Processing and Computer Vision | Assignment 7 due Nov 27 |
| Week of Nov 28 | Robotics and robot motion planning | Assignment 8 due Dec 4 |
| Week of Dec 5 | Natural Language Processing and Information Retrieval | |
| Week of Dec 12 | FINAL EXAM due Dec 18 |
| Date | Content | Homework & Exams |
| Week of Oct 3 | Overview of AI, Search | Assignment 1 due Oct 9 |
| Week of Oct 10 | Statistics, Uncertainty, and Bayes networks | Assignment 2 due Oct 16 |
| Week of Oct 17 | Machine Learning | Assignment 3 due Oct 23 |
| Week of Oct 24 | Hidden Markov models and Bayes filters | Assignment 4 due Oct 30 |
| Week of Oct 31 | Markov Decision Porcesses and and Reinforcement Learning | Assignment 5 due Nov 7 |
| Week of Nov 7 | Adversarial planning (games) and belief space planning (POMDPs) | MIDTERM EXAM due Nov 13 |
| Week of Nov 14 | Logic and Logical Problem Solving | Assignment 6 due Nov 20 |
| Week of Nov 21 | Image Processing and Computer Vision | Assignment 7 due Nov 27 |
| Week of Nov 28 | Robotics and robot motion planning | Assignment 8 due Dec 4 |
| Week of Dec 5 | Natural Language Processing and Information Retrieval | |
| Week of Dec 12 | FINAL EXAM due Dec 18 |
