流行的视觉追踪方法

standard mean shift tracker（MS）CVPR-00

“Real-time tracking of non-rigid objects using mean shift”

mean shift tracker（MS）PAMI-03

“Kernel-based object tracking”

covariance tracker（CV）CVPR-06

“Covariance tracking using model update based on lie algebra”

appearance adaptive particle tracker（AAPF）TIP-04

“Visual Tracking and recognition using appearance-adaptive models in particle filters”

ensemble tracker（ES）CVPR-05

“Ensemble Tracking”

L1 tracker ICCV-09

“Robust Visual Tracking using L1 minimization”

visual tracker sampler（VTS）ICCV-11

“Tracking by sampling trackers”

MCMC-method PAMI-05

“MCMC-based particle filtering for tracking a variable number of interacting targets”

Incremental Visual Tracking（IVT）IJCV-08

“Incremental Learning for robust visual tracking”

Multiple Instance Learning（MIL）CVPR-09

“Visual tracking with online multiple instance learning”

Visual Tracking Decomposition（VTD）CVPR-10

“Visual Tracking Decomposition”

Frag tracking CVPR-06

“Robust fragments-based tracking using the integral histogram”

WSL tracker PAMI-03

“Robust online appearance models for visual tracking”

TLD tracker PAMI-12

“Tracking-Learning-Detection”

online boosting BMVC-06

“Real-time Tracking via On-line Boosting”

Semi-boost tracker ECCV-08

“Semi-Supervised On-line Boosting for Robust Tracking”