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» Probabilistic Object Tracking Using Multiple Features
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ICIP
2008
IEEE
14 years 2 months ago
Multi-object tracking using binary masks
In this paper, we introduce a new method for tracking multiple objects. The method combines Kalman filtering and the Expectation Maximization (EM) algorithm in a novel way to dea...
Sami Huttunen, Janne Heikkilä
TIP
2008
157views more  TIP 2008»
13 years 7 months ago
Robust Face Tracking via Collaboration of Generic and Specific Models
Significant appearance changes of objects under different orientations could cause loss of tracking, "drifting." In this paper, we present a collaborative tracking framew...
Peng Wang, Qiang Ji
TMI
2011
147views more  TMI 2011»
13 years 2 months ago
Labeling of Lumbar Discs Using Both Pixel- and Object-Level Features With a Two-Level Probabilistic Model
Abstract—Backbone anatomical structure detection and labeling is a necessary step for various analysis tasks of the vertebral column. Appearance, shape and geometry measurements ...
Raja' S. Alomari, Jason J. Corso, Vipin Chaudhary
BMVC
2001
13 years 10 months ago
Adaptive Visual System for Tracking Low Resolution Colour Targets
This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available....
Pakorn KaewTrakulPong, Richard Bowden
IJCV
2006
100views more  IJCV 2006»
13 years 7 months ago
A General Framework for Combining Visual Trackers - The "Black Boxes" Approach
Abstract. Over the past few years researchers have been investigating the enhancement of visual tracking performance by devising trackers that simultaneously make use of several di...
Ido Leichter, Michael Lindenbaum, Ehud Rivlin