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TROB
2008
118views more  TROB 2008»
13 years 6 months ago
A New Kalman-Filter-Based Framework for Fast and Accurate Visual Tracking of Rigid Objects
The best of Kalman-filter-based frameworks reported in the literature for rigid object tracking work well only if the object motions are smooth (which allows for tight uncertainty ...
Youngrock Yoon, Akio Kosaka, Avinash C. Kak
IVC
2008
101views more  IVC 2008»
13 years 6 months ago
Occlusion analysis: Learning and utilising depth maps in object tracking
Complex scenes such as underground stations and malls are composed of static occlusion structures such as walls, entrances, columns, turnstiles and barriers. Unless this occlusion...
Darrel Greenhill, John-Paul Renno, James Orwell, G...
JMM2
2006
141views more  JMM2 2006»
13 years 6 months ago
Human Tracking by Fast Mean Shift Mode Seeking
Change detection by background subtraction is a common approach to detect moving foreground. The resulting difference image is usually thresholded to obtain objects based on pixel ...
Csaba Beleznai, Bernhard Frühstück, Hors...
ICASSP
2011
IEEE
12 years 10 months ago
A general Bayesian algorithm for visual object tracking based on sparse features
This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...
Mauricio Soto Alvarez, Carlo S. Regazzoni
ICMCS
2009
IEEE
219views Multimedia» more  ICMCS 2009»
13 years 3 months ago
Moving targets labeling and correspondence over multi-camera surveillance system based on Markov network
In this paper, we propose an efficient way to simultaneously label and map targets over a multi-camera surveillance system. In the system, we first fuse the detection results from...
Chingchun Huang, Sheng-Jyh Wang