Translational and rotational jitter invariant incremental principal component pursuit for video background modeling

Paul Rodriguez; Brendt Wohlberg

doi:10.1109/ICIP.2015.7350856

Translational and rotational jitter invariant incremental principal component pursuit for video background modeling

Paul Rodriguez, Brendt Wohlberg

Sección de Electricidad y Electrónica

Los Alamos National Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

35 Scopus citations

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.

Original language	English
Title of host publication	2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
Publisher	IEEE Computer Society
Pages	537-541
Number of pages	5
ISBN (Electronic)	9781479983391
DOIs	https://doi.org/10.1109/ICIP.2015.7350856
State	Published - 9 Dec 2015
Event	IEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada Duration: 27 Sep 2015 → 30 Sep 2015

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
Volume	2015-December
ISSN (Print)	1522-4880

Conference

Conference	IEEE International Conference on Image Processing, ICIP 2015
Country/Territory	Canada
City	Quebec City
Period	27/09/15 → 30/09/15

Keywords

Principal Component Pursuit
Rigid transformations
Video Background Modeling

Access to Document

10.1109/ICIP.2015.7350856

Cite this

Rodriguez, P., & Wohlberg, B. (2015). Translational and rotational jitter invariant incremental principal component pursuit for video background modeling. In 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings (pp. 537-541). Article 7350856 (Proceedings - International Conference on Image Processing, ICIP; Vol. 2015-December). IEEE Computer Society. https://doi.org/10.1109/ICIP.2015.7350856

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title = "Translational and rotational jitter invariant incremental principal component pursuit for video background modeling",

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.",

keywords = "Principal Component Pursuit, Rigid transformations, Video Background Modeling",

author = "Paul Rodriguez and Brendt Wohlberg",

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year = "2015",

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doi = "10.1109/ICIP.2015.7350856",

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Rodriguez, P & Wohlberg, B 2015, Translational and rotational jitter invariant incremental principal component pursuit for video background modeling. in 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings., 7350856, Proceedings - International Conference on Image Processing, ICIP, vol. 2015-December, IEEE Computer Society, pp. 537-541, IEEE International Conference on Image Processing, ICIP 2015, Quebec City, Canada, 27/09/15. https://doi.org/10.1109/ICIP.2015.7350856

Translational and rotational jitter invariant incremental principal component pursuit for video background modeling. / Rodriguez, Paul; Wohlberg, Brendt.
2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings. IEEE Computer Society, 2015. p. 537-541 7350856 (Proceedings - International Conference on Image Processing, ICIP; Vol. 2015-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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Rodriguez P, Wohlberg B. Translational and rotational jitter invariant incremental principal component pursuit for video background modeling. In 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings. IEEE Computer Society. 2015. p. 537-541. 7350856. (Proceedings - International Conference on Image Processing, ICIP). doi: 10.1109/ICIP.2015.7350856

Translational and rotational jitter invariant incremental principal component pursuit for video background modeling

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