Real-Time Tracking via On-line Boosting

Summary

A novel on-line AdaBoost feature selection algorithm for tracking that allows to adapt the classifier while tracking the object and selects the most features for tracking resulting in stable tracking results.

Keywords

Boosting (machine learning), Computer science, Artificial intelligence, Tracking (education), Computer vision

References

Computer Vision Face Tracking For Use in a Perceptual User InterfaceR. Bradski Gary — 1998
Mean shift analysis and applicationsDorin Comaniciu, Peter Meer — 1999
Detecting Pedestrians Using Patterns of Motion and AppearancePaul Viola, Michael Jones, Daniel Snow — 2003
The template update problemIain Matthews, Takuji Ishikawa, Sara M. Baker — 2004
On-line selection of discriminative tracking featuresCollins, Liu — 2003
Robust online appearance models for visual trackingAllan D. Jepson, David J. Fleet, T.R. El-Maraghi — 2001
Efficient Region Tracking With Parametric Models of Geometry and IlluminationGregory D. Hager, Peter N. Belhumeur — 1998
On-line density-based appearance modeling for object trackingBohyung Han, L.S. Davis — 2005
Incremental Learning for Visual TrackingJongwoo Lim, David A. Ross, Ruei-Sung Lin — 2004
Probabilistic tracking in joint feature-spatial spacesAhmed Elgammal, Ramani Duraiswami, L.S. Davis — 2003
Online selecting discriminative tracking features using particle filterJianyu Wang, Xilin Chen, Wen Gao — 2005
Learning object detection from a small number of examples: the importance of good featuresK. Levi, Yaakov Weiss — 2004
Visual tracking using learned linear subspacesJ. Ho, Kuang-Chih Lee, Ming–Hsuan Yang — 2004
Integral histogram: a fast way to extract histograms in Cartesian spacesFatih Porikli — 2005
Sparse Bayesian learning for efficient visual trackingOliver Williams, Andrew Blake, Roberto Cipolla — 2005
Real-time tracking of non-rigid objects using mean shiftDorin Comaniciu, Visvanathan Ramesh, Peter Meer — 2000
Histograms of oriented gradients for human detectionNavneet Dalal, Bill Triggs — 2005
Support vector trackingShai Avidan — 2004
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary PatternsTimo Ojala, Matti Pietikäinen, Topi Mäenpää — 2002
Learning a Rare Event Detection Cascade by Direct Feature SelectionJianxin Wu, James M. Rehg, Matthew D. Mullin — 2003

Cited by

NUS-PRO: A New Visual Tracking ChallengeSilvia Lidia González — 2016
Fast Simultaneous Tracking and Recognition Using Incremental Keypoint MatchingJonathan Mooser, Quan Wang, Suya You — 2008
Multiple-cue Face Tracking using Particle Filter Embedded in Incremental Discriminant ModelsZi-Yang Liu, Ju-Chin Chen, Jenn-jier James Lien — 2010
On-line Boosting Learning for Hand Tracking and RecognitionNguyen Dang Binh, Nguyễn Thị Thanh Thủy, Horst Bischof — 2008
EnMS: early non-maxima suppressionAdam Herout, Michal Hradiš, Pavel Zemčík — 2012
Interpreting Structures in Man-made Scenes - Combining Low-Level and High-Level Structure SourcesKasim Terzić, Lothar Hotz, J Šochman — 2010
A Study of Exploiting Objectness for Robust Online Object TrackingRaghu Kiran Yalamanchili — 2013
Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series DataNaiyan Wang, Dit‐Yan Yeung — 2014
Dynamic ensemble for target trackingIngrid Visentini, Lauro Snidaro, Gian Luca Foresti — 2008
Object tracking: Appearance modeling and feature learningRaed Almomani — 2015
Integrating Geometric, Motion and Appearance Constraints for Robust Tracking in Aerial VideosMahmudul Hasan — 2013
Robust visual tracking via online multiple instance learning with Fisher informationChao Xu, Wenyuan Tao, Zhaopeng Meng — 2015
Robust tracking based on local structural cell graphHeng Fan, Jinhai Xiang, Honghong Liao — 2015
Robust Tracking through LearningAlessandro Pieropan, Niklas Bergström, Hedvig Kjellström — 2014
The State-of-the-Art in Handling Occlusions for Visual Object TrackingKourosh Meshgi, Shin Ishii — 2015
Online structured learning for real-time computer vision gaming applicationsSam Hare — 2012
Multi-local-task learning with global regularization for object trackingShunli Zhang, Yao Sui, Sicong Zhao — 2015
Adaptive visual samplingYogesh Raja — 2010
Multi-Task Object Tracking with Feature SelectionXu Cheng, Nijun Li, Tongchi Zhou — 2015
An Adaptive Method of Tracking Anatomical Curves in X-Ray SequencesYu Cao, Peng Wang — 2012

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