Abstract
Background subtraction is one of the most commonly used components in machine vision systems. Despite the numerous algorithms proposed in the literature and used in practical applications, key challenges remain in designing a single system that can handle diverse environmental conditions. In this paper we present Multiple Background Model based Background Subtraction Algorithm as such a candidate. The algorithm was originally designed for handling sudden illumination changes. The new version has been refined with changes at different steps of the process, specifically in terms of selecting optimal color space, clustering of training images for Background Model Bank and parameter for each channel of color space. This has allowed the algorithm's applicability to wide variety of challenges associated with change detection including camera jitter, dynamic background, Intermittent Object Motion, shadows, bad weather, thermal, night videos etc. Comprehensive evaluation demonstrates the superiority of algorithm against state of the art.
Original language | English |
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Title of host publication | 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings |
Pages | 4530-4534 |
Number of pages | 5 |
ISBN (Electronic) | 9781479983391 |
DOIs | |
State | Published - Dec 9 2015 |
Event | IEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada Duration: Sep 27 2015 → Sep 30 2015 |
Publication series
Name | Proceedings - International Conference on Image Processing, ICIP |
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Volume | 2015-December |
ISSN (Print) | 1522-4880 |
Conference
Conference | IEEE International Conference on Image Processing, ICIP 2015 |
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Country/Territory | Canada |
City | Quebec City |
Period | 9/27/15 → 9/30/15 |
Bibliographical note
Publisher Copyright:© 2015 IEEE.
Keywords
- Background Subtraction
- background model bank
- background modelling
- binary classifiers
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Signal Processing