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» A Filter Object Framework for MICO
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TSP
2010
13 years 10 days ago
Bayesian multi-object filtering with amplitude feature likelihood for unknown object SNR
In many tracking scenarios, the amplitude of target returns are stronger than those coming from false alarms. This information can be used to improve the multi-target state estimat...
Daniel Clark, Branko Ristic, Ba-Ngu Vo, Ba-Tuong V...
TROB
2008
118views more  TROB 2008»
13 years 5 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

Publication
264views
13 years 2 months ago
Combined feature evaluation for adaptive visual object tracking
Existing visual tracking methods are challenged by object and background appearance variations, which often occur in a long duration tracking. In this paper, we propose a combined ...
Zhenjun Han, Qixiang Ye, Jianbin Jiao
ICIP
2005
IEEE
14 years 7 months ago
Bayesian visual tracking with existence process
Most object tracking approaches either assume that the number of objects is constant, or that information about object existence is provided by some external source. Here, we show...
Jaco Vermaak, Mark Briers, Patrick Pérez, S...
ICIAR
2005
Springer
13 years 11 months ago
A Novel Tracking Framework Using Kalman Filtering and Elastic Matching
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is genera...
Xingzhi Luo, Suchendra M. Bhandarkar