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» Online Empirical Evaluation of Tracking Algorithms
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ICCV
2007
IEEE
16 years 1 months ago
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
ECCV
2008
Springer
16 years 1 months ago
Robust Visual Tracking Based on an Effective Appearance Model
Most existing appearance models for visual tracking usually construct a pixel-based representation of object appearance so that they are incapable of fully capturing both global an...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang
ICONIP
2009
14 years 9 months ago
Tracking in Reinforcement Learning
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
FTCS
1993
123views more  FTCS 1993»
15 years 29 days ago
Fast, On-Line Failure Recovery in Redundant Disk Arrays
This paper describes and evaluates two algorithms for performing on-line failure recovery (data reconstruction) in redundant disk arrays. It presents an implementation of disk-ori...
Mark Holland, Garth A. Gibson, Daniel P. Siewiorek
ACCV
2007
Springer
15 years 5 months ago
Spatiotemporal Oriented Energy Features for Visual Tracking
This paper presents a novel feature set for visual tracking that is derived from “oriented energies”. More specifically, energy measures are used to capture a target’s multi...
Kevin Cannons, Richard Wildes