Incremental Learning for Robust Visual Tracking

Abstract

Visual tracking, in essence, deals with non-stationary image streams that change over time. While most existing algorithms are able to track objects well in controlled environments, they usually fail in the presence of significant variation of the object’s appearance or surrounding illumination. One reason for such failures is that many algorithms employ… (More)
DOI: 10.1007/s11263-007-0075-7

Topics

11 Figures and Tables

Statistics

020040020082009201020112012201320142015201620172018
Citations per Year

2,168 Citations

Semantic Scholar estimates that this publication has 2,168 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Ross2007IncrementalLF, title={Incremental Learning for Robust Visual Tracking}, author={David A. Ross and Jongwoo Lim and Ruei-Sung Lin and Ming-Hsuan Yang}, journal={International Journal of Computer Vision}, year={2007}, volume={77}, pages={125-141} }