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» Bayesian Framework for Video Surveillance Application
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ACIVS
2005
Springer
13 years 11 months ago
A Hybrid Color-Based Foreground Object Detection Method for Automated Marine Surveillance
This paper proposes a hybrid foreground object detection method suitable for the marine surveillance applications. Our approach combines an existing foreground object detection met...
Daniel Socek, Dubravko Culibrk, Oge Marques, Hari ...
ACIVS
2009
Springer
14 years 25 days ago
Comparing Feature Matching for Object Categorization in Video Surveillance
In this paper we consider an object categorization system using local HMAX features. Two feature matching techniques are compared: the MAX technique, originally proposed in the HMA...
Rob G. J. Wijnhoven, Peter H. N. de With
AVSS
2005
IEEE
13 years 12 months ago
Performance evaluation of event detection solutions: the CREDS experience
In video surveillance projects, automatic and realtime event detection solutions are required to guarantee an efficient and cost-effective use of the infrastructure. Many solution...
Francesco Ziliani, Sergio A. Velastin, Fatih Porik...
ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
13 years 4 months ago
Modeling and decision making in spatio-temporal processes for environmental surveillance
Abstract— The need for efficient monitoring of spatiotemporal dynamics in large environmental surveillance applications motivates the use of robotic sensors to achieve sufficie...
Amarjeet Singh 0003, Fabio Ramos, Hugh D. Whyte, W...
ICPR
2008
IEEE
14 years 20 days ago
Robust estimation of foreground in surveillance videos by sparse error estimation
Frames of videos with static background and dynamic foreground can be viewed as samples of signals that vary slowly in time with sparse corruption caused by foreground objects. We...
Mert Dikmen, Thomas S. Huang