Video Tracking in Complex Scenes for Surveillance Applications
Call for Papers
Tracking moving objects is one of the basic tasks performed by surveillance systems. The target current position and its movement are relevant information to fulfil several applications as activity analysis, objects counting, identification, stolen object detection, and so forth. Many tracking algorithms have been applied for surveillance applications. However when the scene/situation is “complex,” the performances relevantly decrease affecting consequently further surveillance functionalities.
In this domain of applications, the complexity of a perceived scene/situation can present multiple aspects as, just to give some examples:
- high number of distracting moving targets
- multisensor video setup
- static and dynamic nonstationary occlusions
- 24-hour all-weathers outdoor functioning
- complex backgrounds
This special issue is oriented to provide a self-contained framework to address recent research results towards novel methods proposed in recent years to improve object tracking performances in complex scenes; in particular a (nonrestrictive) list of relevant topics follows, which can be addressed in the proposed contributions:
- Bayesian method for conjunctive multitarget tracking
- kernel-based method for multitarget tracking
- feature-based algorithm for multitarget tracking
- feature selection for tracking
- collaborative trackers
- online tracking parameters regulation
- definition of metrics for evaluating the complexity of the scene/situation
- definition of metrics for evaluating the performance of multitarget trackers
Authors should follow the EURASIP Journal on Image and Video Processing manuscript format described at the journal site http://www.hindawi.com/journals/ivp/. Prospective authors should submit an electronic copy of their complete manuscripts through the journal Manuscript Tracking System at http://mts.hindawi.com/, according to the following timetable:
| Manuscript Due | November 1, 2007 |
| First Round of Reviews | February 1, 2008 |
| Publication Date | May 1, 2008 |
Guest Editors:
- Andrea Cavallaro, Department of Electronic Engineering, Queen Mary, University of London, London E1 4NS, United Kingdom
- Fatih Porikli, Mitsubishi Electric Research Laboratories (MERL), Mitsubishi Electric Corporation, Cambridge, MA 02139, USA
- Carlo S. Regazzoni, Department of Biophysical and Electronic Engineering, University of Genova, 16145 Genova, Italy