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» Likelihood Map Fusion for Visual Object Tracking
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ICPR
2006
IEEE
14 years 8 months ago
Non-overlapping Distributed Tracking using Particle Filter
Tracking people or objects across multiple cameras is a challenging research area in visual computing especially when these cameras have non-overlapping field-of-views. The import...
Fee-Lee Lim, Tele Tan, Wilson S. Leoputra
ECCV
2008
Springer
14 years 9 months ago
Robust Visual Tracking Based on an Effective Appearance Model
Most existing appearance models for visual tracking usually construct a pixel-based representation of object appearance so that they are incapable of fully capturing both global an...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang
IFIP
2010
Springer
14 years 10 days ago
Grasp Exploration for 3D Object Shape Representation Using Probabilistic Map
In this work it is shown the representation of 3D object shape acquired from grasp exploration. Electromagnetic motion tracking sensors are used on the fingers for object contour f...
Diego R. Faria, Ricardo Martins, Jorge Dias
CVPR
2000
IEEE
13 years 12 months ago
Adaptive Bayesian Recognition in Tracking Rigid Objects
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
Yuri Boykov, Daniel P. Huttenlocher
CVPR
2004
IEEE
14 years 9 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong