Network surveillance cameras
MSc dissertation proposal 2012/2013
Multi-tasking
Smart Cameras
Introduction:
The increasing need of surveillance in public spaces and the recent technological
advances on embedded video compression and communications made camera networks
ubiquitous. Most of nowadays surveillance cameras are however still very
conventional: imaging resolution is usually 640x480 (or less) to keep low
bandwidth usage, pan-tilt-zoom are manually driven, fisheye lenses wider than 180deg are not
common due to a harder interpretation by humans, etc.
This project proposal is focused on removing some of the restrictions.
The interfacing standard is network based (i.e. considering IP cameras), and it
is assumed that some processing can be handled in the camera (IP cameras
usually have a computer inside running linux) or by a
dedicated (buffering) computer. Some restrictions to remove include maintaining scene
representations on the camera and implementing some automatic
surveillance / monitoring behaviours.
Note:
this project is proposed in the framework of two projects, a national project
on camera modelling and calibration, DCCAL, and
an EU financed project (QREN) on modelling and using high-definition
surveillance cameras, HDA.
Objectives:
The main objectives of this project are: (i) interfacing
to novel IP cameras, (ii) calibrating the cameras, and (iii) multi-tasking
surveillance or monitoring
behaviours.
Detailed description:
This project proposal is focused on modelling and operating network (IP)
cameras, and placing memory and processing capabilities on the camera or on a dedicated
(buffering) computer. The IP camera interfaces are currently
receiving much attention in the form of a large consensus on what their
interfacing standard should be. Major surveillance / IP camera manufacturers
have recently introduced the ONVIF standard [ONVIF-www] which has effectively
the capabilities to be a global standard on the video surveillance market.
Placing memory and processing on the cameras, or buffering computers,
has clear advantages on keeping low bandwidth requirements. Some of the working
directions come from video encoding technologies. For example saving locally
background images allows sending just incremental changes. Compensating imaging
artefacts and tracking moving objects are additional methodologies allowing
bandwidth saving, and therefore incorporating high-definition cameras within
the currently installed networking hardware.
Exchanging information directly among the cameras is another way to save
network bandwidth. Handing over events among cameras, e.g. informing of moving
objects that are expected to enter the field of view of neighbouring cameras,
usually involves calibrating the camera-network. Given a number of
reconstructed 3D-points of the environment and their images we can calibrate the
network of cameras using standard computer vision methodologies [Hartley00].
This is also one aspect to focus in this project proposal.
In summary, this project proposal involves:
1) Developing a software interface to novel high-definition IP cameras
2) Calibrating the individual cameras and the camera-network
3) Detecting and tracking moving objects; monitoring of tracked events
over the camera network
References:
[Hartley00] R. I. Hartley and
[LoweWWW]
David G. Lowe. Demo software: Sift keypoint detector.
http://www.cs.ubc.ca/˜lowe/keypoints/.
[Axis] IP camera manufacturer
actively involved in the definition of the ONVIF standard http://www.axis.com/pt/onvif/index.htm
[ONVIF-www] open industry
forum for the development of a global standard for the interface of IP-based physical
security products http://www.onvif.org/
[Starzyk11] "Multi-tasking Smart Cameras for Intelligent Video
Surveillance Systems", Wiktor Starzyk, Faisal Z. Qureshi, 8th
IEEE International Conference on Advanced Video and Signal-Based Surveillance,
2011.
Requirements (grades, required courses, etc):
-
Expected results:
At the end of the work, the students will have enriched their experience
in computer vision applied to surveillance camera setups.
Place for conducting the work-proposal:
ISR / IST
More MSc dissertation
proposals on Computer and Robot Vision in:
http://omni.isr.ist.utl.pt/~jag