A Matlab implementation of a fast incremental principal component pursuit algorithm for Video Background Modeling

Cite Details

Paul Rodríguez and Brendt Wohlberg, "A Matlab implementation of a fast incremental principal component pursuit algorithm for Video Background Modeling", in Proceedings of IEEE International Conference on Image Processing (ICIP), (Paris, France), doi:10.1109/ICIP.2014.7025692, pp. 3414--3416, Oct 2014

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Abstract

In this proposal we present a Matlab-only implementation of a simple, novel, and fully incremental Principal Component Pursuit (PCP) algorithm for Video Background Modeling. Our implementation can process full HD color 1920 × 1088 videos at a rate of 0.61 seconds per frame running on a standard laptop (Intel i7-2670QM quad-core, 6GB RAM, 2.2 GHz). Unlike other incremental or online PCP-like algorithms, such as ReProCS, GRASTA or pROST, the initialization stage of our implementation is extremely fast, has modest memory requirements (6.5 seconds and less than 0.5 Gb for a full HD video), and is also able to quickly adapt to changes in the background. Moreover our implementation can also process live-feed videos, which in our proposed demonstration will be acquired via a wireless camera, resulting in an interactive demonstration where the the moving objects to be segmented are the audience.

BibTeX Entry

@inproceedings{rodriguez-2014-matlab,

author = {Paul Rodr\'{i}guez and Brendt Wohlberg},

title = {A {M}atlab implementation of a fast incremental principal component pursuit algorithm for Video Background Modeling},

year = {2014},

month = Oct,

urlpdf = {http://brendt.wohlberg.net/publications/pdf/rodriguez-2014-matlab.pdf},

booktitle = {Proceedings of IEEE International Conference on Image Processing (ICIP)},

address = {Paris, France},

doi = {10.1109/ICIP.2014.7025692},

pages = {3414--3416}

}