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CVPR
2009
IEEE
15 years 2 months ago
Learning to Track with Multiple Observers
We propose a novel approach to designing algorithms for object tracking based on fusing multiple observation models. As the space of possible observation models is too large for...
Björn Stenger, Roberto Cipolla, Thomas Woodle...
ECCV
2002
Springer
14 years 9 months ago
Towards Improved Observation Models for Visual Tracking: Selective Adaptation
Abstract. An important issue in tracking is how to incorporate an appropriate degree of adaptivity into the observation model. Without any adaptivity, tracking fails when object pr...
Andrew Blake, Jaco Vermaak, Michel Gangnet, Patric...
AIPS
2007
13 years 10 months ago
Using Adaptive Priority Weighting to Direct Search in Probabilistic Scheduling
Many scheduling problems reside in uncertain and dynamic environments – tasks have a nonzero probability of failure and may need to be rescheduled. In these cases, an optimized ...
Andrew M. Sutton, Adele E. Howe, L. Darrell Whitle...
ICIP
2003
IEEE
14 years 9 months ago
Transductive inference for color-based particle filter tracking
Robust real-time tracking of non-rigid objects in a dynamic environment is a challenging task. Among various cues in tracking, color can provide an efficient visual cue for this t...
Jiang Li, Chin-Seng Chua
ICPR
2004
IEEE
14 years 8 months ago
Evaluation of Three Optical Flow-Based Observation Models for Tracking
In this paper, we study the use of optical flow as a characteristic for tracking. We analyze the behavior of three flowbased observation models for particle filter algorithms, and...
José M. Fuertes, Manuel J. Lucena, Nicolas ...