Fast Moving Objects Detection Using iLBP Background Model

Clicks: 222
ID: 21767
2014
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #52 of 81 articles by views in the international archives of the photogrammetry, remote sensing and spatial information sciences

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
In this paper a new approach for moving objects detection in video surveillance systems is proposed. It is based on iLBP (intensity local binary patterns) descriptor that combines the classic LBP (local binary patterns) and the multiple regressive pseudospectra model. The iLBP descriptor itself is considered together with computational algorithm that is based on the sign image representation. We show that motion analysis methods based on iLBP allow uniformly detecting objects that move with different speed or even stop for a short while along with unattended objects. We also show that proposed model is comparable to the most popular modern background models, but is significantly faster.
Reference Key
vishnyakov2014fastthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Vishnyakov, B.;Gorbatsevich, V.;Sidyakin, S.;Vizilter, Y.;Malin, I.;Egorov, A.;
Journal the international archives of the photogrammetry, remote sensing and spatial information sciences
Year 2014
DOI
DOI not found
URL
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3/347/2014/isprsarchives-XL-3-347-2014.pdf
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.