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» Multiple Object Tracking with Kernel Particle Filter
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NIPS
2004
13 years 9 months ago
Incremental Learning for Visual Tracking
Most existing tracking algorithms construct a representation of a target object prior to the tracking task starts, and utilize invariant features to handle appearance variation of...
Jongwoo Lim, David A. Ross, Ruei-Sung Lin, Ming-Hs...
TSP
2010
13 years 2 months 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...
ICCV
2011
IEEE
11 years 11 months ago
Action Recognition in Videos Acquired by a Moving Camera Using Motion Decomposition of Lagrangian Particle Trajectories
Recognition of human actions in a video acquired by a moving camera typically requires standard preprocessing steps such as motion compensation, moving object detection and object ...
Shandong Wu, Omar Oreifej, and Mubarak Shah
IJCV
2000
161views more  IJCV 2000»
13 years 7 months ago
Probabilistic Detection and Tracking of Motion Boundaries
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Michael J. Black, David J. Fleet
TSP
2008
139views more  TSP 2008»
13 years 7 months ago
Bayesian Filtering With Random Finite Set Observations
This paper presents a novel and mathematically rigorous Bayes recursion for tracking a target that generates multiple measurements with state dependent sensor field of view and clu...
Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni