Background difference example

MSc dissertation proposal 2007/2008

 

Target Detection using Adaptive Background Models

 

 

Introduction:

 

"Although surveillance cameras are already prevalent in banks, stores, and parking lots, video data currently is used only -after the fact- as a forensic tool, thus losing its primary benefit as an active, real-time medium. (...)"

[introduction of the Video Surveillance And Monitoring project - http://www.cs.cmu.edu/~vsam/index.html]

 

Today we assist to cameras installed everywhere; however we find that most of them are unattended due to the very high costs of having humans watching the huge amounts of the resulting video-imaging. In this work we propose building an automatic target detection method, in order to minimize the surveillance work done by humans, and in addition using pan-tilt-zoom (PTZ) cameras which allow simultaneously covering large surveillance areas and observing regions of interest in detail.

 

 

Objectives:

 

The goals of this work proposal are two-fold: (i) building high-resolution multiscale panoramic mosaics from pan-tilt-zoom cameras, (ii) detecting intrusions on the mosaics.

 

 

Detailed description:

 

As noted in the introduction, automatic target detection is a required feature of modern video surveillance systems. Target detection on large areas involves using many cameras. Alternatively, as proposed in this work, one can use pan-tilt-zoom (PTZ) cameras, i.e. mobile cameras with the elevation, azimuth and zoom degrees of freedom, which allow simultaneously observing large (typically) static scenarios and seeing in detail small portions where e.g. intrusion events were detected.

 

Most PTZ cameras closely resemble central cameras, in the sense that despite changing their elevation and azimuth angles, the imaging does not suffer (significant) parallax effects. This property, combined with (almost) static scenarios, allows constructing simple background-representations of the environment as the so termed video mosaics.

 

Video mosaics consist of enlarged images of the scene obtained through the composition of individual (smaller field of view) images. When using PTZ cameras, mosaics are built iteratively by rotating the camera to cover the complete field of view.

 

This work-proposal encompasses therefore two main steps:

 

(i) Build high-resolution multiscale panoramic mosaics from PTZ cameras - In order to build mosaics from PTZ cameras, it is necessary to calibrate the cameras' internal parameters using video information (better accuracy than using the internal readings of the camera pose [Sinha04]) and then registering the views acquired at different orientations.

 

(ii) Detect intrusions on the mosaics - Detecting intrusions on the scene involves detecting changing pixels, pixel-grouping to regions and regions-filtering to remove non-relevant too small detections [Boult01]. The mosaic (background model) has to be updated in order to deal with e.g. with illumination or scene content changes.

 

References:

[Sinha04] S Sinha, M Pollefeys, "Towards Calibrating a Pan-Tilt-Zoom Camera Network", OMNIVIS'04 (with ECCV'04)

[Hall05] "Comparison of target detection algorithms using adaptive background models", D. Hall, J. Nascimento, P. Ribeiro, E. Andrade, P. Moreno, S. Pesnel, T. List, R. Emonet, R.B. Fisher, J. Santos Victor, J. Crowley, Int. workshop on Performance evaluation of Tracking and Surveillance - Oct 2005

[Boult01] “Into the woods: Visual surveillance of non-cooperative camouflaged targets in complex outdoor settings,” T. Boult, R. Micheals, X. Gao, and M. Eckmann, Proc. IEEE, pp. 1382–1402, Oct. 2001.

[Nascimento06] "Performance Evaluation of Object Detection Algorithms for Video Surveillance", Nascimento, J.C.; Marques, J.S.; IEEE T-Multimedia, V8.4, 2006 pp:761 - 774.

 

 

Requirements (Requisitos, e.g. média,disciplinas concluídas):

 

 

Expected results (Resultado esperado):

 

At the end of the work, the students will have enriched their experience in computer vision applied to video surveillance setups. In particular are expected to:

- developed geometric modelling methods for pan-tilt-zoom cameras

- algorithms for intrusion detection and tracking.

 

 

Workplace (Local realização da dissertação):

ISR / IST

 

 

More MSc dissertation proposals on Computer and Robot Vision in:

 

http://omni.isr.ist.utl.pt/~jag