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» Adaptive Background Mixture Models for Real-Time Tracking
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IROS
2006
IEEE
139views Robotics» more  IROS 2006»
14 years 1 months ago
Tracking Articulating Objects from Ground Vehicles using Mixtures of Mixtures
— An algorithm for tracking articulating objects from moving camera platforms is presented. Mixtures of mixtures are used to model the appearance of the object and the background...
Wael Abd-Almageed, Mohamed E. Hussein, Larry S. Da...
CVPR
2000
IEEE
14 years 9 months ago
Statistical Modeling and Performance Characterization of a Real-Time Dual Camera Surveillance System
The engineering of computer vision systems that meet application speci c computational and accuracy requirements is crucial to the deployment of real-life computer vision systems....
Michael Greiffenhagen, Visvanathan Ramesh, Dorin C...
AVSS
2009
IEEE
13 years 8 months ago
Robust Vehicle Detection for Tracking in Highway Surveillance Videos Using Unsupervised Learning
This paper presents a novel approach to vehicle detection in highway surveillance videos. This method incorporates well-studied computer vision and machine learning techniques to ...
Birgi Tamersoy, Jake K. Aggarwal
PRL
2006
153views more  PRL 2006»
13 years 7 months ago
Efficient adaptive density estimation per image pixel for the task of background subtraction
We analyze the computer vision task of pixel-level background subtraction. We present recursive equations that are used to constantly update the parameters of a Gaussian mixture m...
Zoran Zivkovic, Ferdinand van der Heijden
RTAS
2007
IEEE
14 years 1 months ago
An Approach for Real-Time Database Modeling and Performance Management
It is challenging to manage the performance of real-time databases (RTDBs) that are often used in data-intensive real-time applications such as agile manufacturing and target trac...
Jisu Oh, Kyoung-Don Kang