AMBER: Adapting multi-resolution background extractor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a fast self-adapting multi-resolution background detection algorithm is introduced. A pixel-based background model is proposed, that represents not only each pixel's background values, but also their efficacies, so that new background values always replace the least effective ones. Model maintenance and global control processes ensure fast initialization, adaptation to background changes with different timescales, restrain the generation of ghosts, and adjust the decision thresholds based on noise levels. Evaluation results indicate that the proposed algorithm outperforms most other state-of-the-art algorithms not only in terms of accuracy, but also in terms of processing speed and memory requirements.

Bibliographical metadata

Original languageEnglish
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013
Pages3417-3421
DOIs
Publication statusPublished - 2013
Event2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC
Event duration: 1 Jul 2013 → …

Conference

Conference2013 20th IEEE International Conference on Image Processing, ICIP 2013
CityMelbourne, VIC
Period1/07/13 → …