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» Online Empirical Evaluation of Tracking Algorithms
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ICPR
2008
IEEE
14 years 7 months ago
Training sequential on-line boosting classifier for visual tracking
On-line boosting allows to adapt a trained classifier to changing environmental conditions or to use sequentially available training data. Yet, two important problems in the on-li...
Helmut Grabner, Horst Bischof, Jan Sochman, Jiri M...
WWW
2010
ACM
14 years 23 days ago
Tracking the random surfer: empirically measured teleportation parameters in PageRank
PageRank computes the importance of each node in a directed graph under a random surfer model governed by a teleportation parameter. Commonly denoted alpha, this parameter models ...
David F. Gleich, Paul G. Constantine, Abraham D. F...
CVPR
2009
IEEE
15 years 27 days 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...
ENDM
2010
130views more  ENDM 2010»
13 years 5 months ago
Experimental Analysis of an Online Trading Algorithm
Trading decisions in financial markets can be supported by the use of online algorithms. We evaluate the empirical performance of a threat-based online algorithm and compare it to...
Günter Schmidt, Esther Mohr, Mike Kersch
CVPR
2006
IEEE
13 years 12 months ago
A Modular Approach to the Analysis and Evaluation of Particle Filters for Figure Tracking
This paper presents the first systematic empirical study of the particle filter (PF) algorithms for human figure tracking in video. Our analysis and evaluation follows a modula...
Ping Wang, James M. Rehg