Los Alamos National Laboratory
Phone| Search
T-5 HomeResearchPublications › rodriguez-2015-translational
› Contact › People › Research
› Projects › Highlights › Publications
› Jobs › Visitor Info

Cite Details

Paul Rodríguez and Brendt Wohlberg, "Translational and Rotational Jitter Invariant Incremental Principal Component Pursuit for Video Background Modeling", in Proceedings of IEEE International Conference on Image Processing (ICIP), (Québec City, Québec, Canada), doi:10.1109/ICIP.2015.7350856, pp. 537--541, Sep 2015

Abstract

While Principal Component Pursuit (PCP) is currently considered to be the state of the art method for video background modeling, it suffers from a number of limitations, including a high computational cost, a batch operating mode, and sensitivity to camera jitter. In this paper we propose a novel fully incremental PCP algorithm for video background modeling that is robust to translational and rotational jitter. It processes one frame at a time, obtaining similar results to standard batch PCP algorithms, while being able to deal with translational and rotational jitter. It also has extremely low memory footprint, and a computational complexity that allows almost real-time processing.

BibTeX Entry

@inproceedings{rodriguez-2015-translational,
author = {Paul Rodr\'{i}guez and Brendt Wohlberg},
title = {Translational and Rotational Jitter Invariant Incremental Principal Component Pursuit for Video Background Modeling},
year = {2015},
month = Sep,
urlpdf = {http://math.lanl.gov/~brendt/Publications/Docs/rodriguez-2015-translational.pdf},
booktitle = {Proceedings of IEEE International Conference on Image Processing (ICIP)},
address = {Qu\'{e}bec City, Qu\'{e}bec, Canada},
doi = {10.1109/ICIP.2015.7350856},
pages = {537--541}
}