Paper Info
Title
Background subtraction with variable illumination in outdoor scenes.
Abstract
Background subtraction is a key prerequisite for intelligent video surveillance, but most of the methods employed are still affected by dynamic changes in the illumination conditions, e.g., shadows cast by passing clouds occur frequently in outdoor scenes. To resolve this problem, a novel approach based on the underlying structure of the difference image is introduced in this study. In particular, local binary patterns (LBPs) are computed based on the frame differencing result, i.e., moving LBP, and then compared with the background model, which is updated according to an online interpolation scheme, in order to determine whether the current pixel belongs to the background. An important advantage of the proposed method is that it efficiently smoothes unexpected noise between frames while also preserving the boundaries of the moving objects by using an edge-aware filtering technique. Experimental results obtained using two benchmark data sets demonstrated that the proposed method is more robust to variable illumination in outdoor scenes compared with previously proposed approaches.
Year
DOI
Venue
2018
10.1007/s11042-017-5410-6
Multimedia Tools Appl.
Keywords
Field
DocType
Background subtraction, Edge-aware filtering, Moving LBP, Variable illumination
Background subtraction,Computer vision,Data set,Pattern recognition,Computer science,Interpolation,Local binary patterns,Filter (signal processing),Artificial intelligence,Pixel
Journal
Volume
Issue
ISSN
77
15
1380-7501
Citations 
PageRank 
References 
0
0.34
32
Authors
1
Name
Order
Citations
PageRank
Wonjun Kim130126.50