Open AccessMUTUAL COMPARATIVE FILTERING FOR CHANGE DETECTION IN VIDEOS WITH UNSTABLE ILLUMINATION CONDITIONS
Author(s) -
S. V. Sidyakin,
B. V. Vishnyakov,
Yu. V. Vizilter,
Nikolay I. Roslov
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b3-535-2016
Subject(s) - normalization (sociology) , change detection , computer science , artificial intelligence , computer vision , transformation (genetics) , mutual information , pattern recognition (psychology) , biochemistry , chemistry , sociology , anthropology , gene
In this paper we propose a new approach for change detection and moving objects detection in videos with unstable, abrupt illumination changes. This approach is based on mutual comparative filters and background normalization. We give the definitions of mutual comparative filters and outline their strong advantage for change detection purposes. Presented approach allows us to deal with changing illumination conditions in a simple and efficient way and does not have drawbacks, which exist in models that assume different color transformation laws. The proposed procedure can be used to improve a number of background modelling methods, which are not specifically designed to work under illumination changes.