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» Probabilistic Object Tracking Using Multiple Features
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ICIP
2007
IEEE
14 years 3 months ago
Mean-Shift Blob Tracking with Adaptive Feature Selection and Scale Adaptation
When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we prop...
Dawei Liang, Qingming Huang, Shuqiang Jiang, Hongx...
ICIP
2008
IEEE
14 years 10 months ago
Live video object tracking and segmentation using graph cuts
Graph cuts have proven to be powerful tools in image segmentation. Previous graph cut research has proposed methods for cutting across large graphs constructed from multiple layer...
Zachary A. Garrett, Hideo Saito
ICIP
2010
IEEE
13 years 7 months ago
A cascaded hierarchical framework for moving object detection and tracking
In this paper we propose a cascaded hierarchical framework for object detection and tracking. We claim that, by integrating both detection and tracking into a unified framework, t...
Chingchun Huang, Sheng-Jyh Wang
ICCV
2003
IEEE
14 years 2 months ago
Tracking Across Multiple Cameras With Disjoint Views
Conventional tracking approaches assume proximity in space, time and appearance of objects in successive observations. However, observations of objects are often widely separated ...
Omar Javed, Zeeshan Rasheed, Khurram Shafique, Mub...
ICCV
2007
IEEE
14 years 11 months ago
Multi-Object Tracking Through Clutter Using Graph Cuts
The standard graph cut technique is a robust method for globally optimal image segmentations. However, because of its global nature, it is prone to capture outlying areas similar ...
Allen Tannenbaum, James G. Malcolm, Yogesh Rathi