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» Tracking Large Variable Numbers of Objects in Clutter
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ICCV
2005
IEEE
14 years 1 months ago
Fast Global Kernel Density Mode Seeking with Application to Localisation and Tracking
We address the problem of seeking the global mode of a density function using the mean shift algorithm. Mean shift, like other gradient ascent optimisation methods, is susceptible...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...
CVPR
2004
IEEE
14 years 9 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
IJCV
2007
118views more  IJCV 2007»
13 years 7 months ago
Disambiguating Visual Motion by Form-Motion Interaction - a Computational Model
The neural mechanisms underlying motion segregation and integration still remain unclear to a large extent. Local motion estimates often are ambiguous in the lack of form features,...
Pierre Bayerl, Heiko Neumann
CIKM
2005
Springer
13 years 9 months ago
DIST: a distributed spatio-temporal index structure for sensor networks
We consider the general problem of tracking moving objects in sensor networks. The specific application we consider is that of tracking a chemical plume moving over a large infra...
Anand Meka, Ambuj K. Singh
JRTIP
2010
137views more  JRTIP 2010»
13 years 2 months ago
Cascaded online boosting
In this paper, we propose a cascaded version of the online boosting algorithm to speed-up the execution time and guarantee real-time performance even when employing a large number ...
Ingrid Visentini, Lauro Snidaro, Gian Luca Foresti