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» Novel Observation Model for Probabilistic Object Tracking
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CVPR
2005
IEEE
14 years 7 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
ECCV
2002
Springer
14 years 7 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...
ICMCS
2006
IEEE
111views Multimedia» more  ICMCS 2006»
13 years 11 months ago
Integration of Background Modeling and Object Tracking
Background model and tracking became critical components for many vision-based applications. Typically, background modeling and object tracking are mutually independent in many ap...
Yu-Ting Chen, Chu-Song Chen, Yi-Ping Hung
TCSV
2008
202views more  TCSV 2008»
13 years 5 months ago
Probabilistic Object Tracking With Dynamic Attributed Relational Feature Graph
Object tracking is one of the fundamental problems in computer vision and has received considerable attention in the past two decades. The success of a tracking algorithm relies on...
Feng Tang, Hai Tao
ECCV
2000
Springer
14 years 7 months ago
A Probabilistic Background Model for Tracking
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
Jens Rittscher, Jien Kato, Sébastien Joga, ...