Video
surveillance at banks, examples of situations to detect automatically
MSc dissertation proposal 2009/2010
Observit
- Video Surveillance for Banks
Introduction:
"For good reason, banks are often seen as the most secure institutions
on the planet. We entrust them with our money, and it's their job to keep it
safe. In order to fulfill this commitment, top-notch
video surveillance systems are a necessity. With recent innovations in digital
technology and IP surveillance, many banks are looking to increase the
effectiveness of their security systems by investing in this new
technology." Excerpt from http://www.videosurveillance.com/banks.asp.
Nowadays, most of the bank facilities have
numerous video surveillance cameras but too few people looking at them. Hence
the chance to detect suspicious behaviours is actually very small. In fact most
of the installed systems lack automatic components in order to detect
unexpected events that may be configuring dangerous situations such as bank
robberies. In this work, the main objective is to study the automatic detection
of a number of unexpected events that may configure bank robbery situations.
This work will be conducted in conjunction
with the company Observit, www.observit.pt,
under a protocol with IST/DEEC.
Supervision: Prof.
José Gaspar, Prof. Alexandre Bernardino, Eng. Bernardo Motta
(Observit)
Objectives:
The objectives of this work are twofold: (i) detecting persons, and (ii) detecting
unexpected events such as faces hidden
under the clothes or people lying on the
floor. At the end of the work it is expected to demonstrate a video
processing tool able to signal the unexpected events in a video sequence.
Detailed description:
Video surveillance for banking applications is still a very active
research-and-development topic mainly because of the large variability of the
installations, fixed/mobile cameras, indoor/outdoor scenarios, etc, and because
of the huge variety of the principal actors, namely people of various heights,
ethnic cultures, ways of dressing, physical impairment, etc, and their actions.
The main objective of this work is the automatic identification of
events that may indicate a bank robbery is undergoing. In this work, the events
to study will be restricted to two important cases: detecting people entering the bank with their faces hidden, and detecting people lying on the floor. Note that while
there are nowadays very efficient face detectors [Viola04, OpenCV], the case of hidden
faces challenges the utilization of those detectors. It is considered an
important part of the project selecting ways to circumvent this problem. One
suggested way starts by the detection of the persons (see [Dollar09]), and then
estimating the face location from the silhouette of each person. In this case,
the face detectors could be once more useful just to determine the low evidence
of visible faces.
The work is therefore organized in the following main steps:
1) Detecting people, using e.g. background subtraction. One specific is of
importance here, namely whether the detection can include outdoor contents
(distracters) such as the imaging provided by windows making the street
visible. In this case discriminating people from mobile objects (e.g. cars) can
benefit from the strategies described in [Figueira09].
2) Detecting the pose of a person, in order to estimate the location of
the face in the image.
3) Verifying that the face is, or is not, visible.
The collaboration with the Observit company, besides bringing to the work references on
commercial systems, is also a contact point with potential clients (banks) for
the system.
References:
[Viola04] "Robust Real-Time Face Detection", Paul Viola and
Michael J. Jones, International Journal of Computer Vision, Vol. 57, No. 2. (1
May 2004), pp. 137-154
[Figueira09] "Optical flow
based detection in mixed human robot environments", D. Figueira,P.
Moreno, A. Bernardino, J. Gaspar, J. Santos-Victor. In Proc. of ISVC 2009 - 5th
International Symposium on Visual Computing, 2009
[Dollar09] "Pedestrian detection: A benchmark", P. Dollar, C. Wojek, B. Schiele, P. Perona, IEEE Conference on Computer Vision and Pattern
Recognition, CVPR 2009, 20-25 June 2009 Page(s):304 - 311
[OpenCV] Open Computer Vision Library, http://sourceforge.net/projects/opencv/
Expected results:
At the end of the work the students will have enriched their knowledge
in:
* Computer vision
* Video Surveillance
Examples of expected demonstrations in simulated and/or real
environments:
* Detections of persons
* Detecting visible / not visible faces in the persons found
Observations:
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More MSc dissertation
proposals on Computer and Robot Vision in:
http://omni.isr.ist.utl.pt/~jag