Paper Info
Title
The Effect of Pixel-Level Fusion on Object Tracking in Multi-Sensor Surveillance Video
Abstract
This paper investigates the impact of pixel-level fusion of videos from visible (VIZ) and infrared (IR) surveillance cameras on object tracking performance, as compared to tracking in single modality videos. Tracking has been accomplished by means of a particle filter which fuses a colour cue and the structural similarity measure (SSIM). The highest tracking accuracy has been obtained in IR sequences, whereas the VIZ video showed the worst tracking performance due to higher levels of clutter. However, metrics for fusion assessment clearly point towards the supremacy of the multiresolutional methods, especially Dual Tree-Complex Wavelet Transform method. Thus, a new, tracking-oriented metric is needed that is able to accurately assess how fusion affects the performance of the tracker.
Year
DOI
Venue
2007
10.1109/CVPR.2007.383433
CVPR
Keywords
Field
DocType
fuses,filtering,particle filter,histograms,wavelet transforms,sensor fusion,video tracking,structural similarity,infrared,object tracking,image resolution
Computer vision,Histogram,Pattern recognition,Computer science,Clutter,Particle filter,Filter (signal processing),Sensor fusion,Video tracking,Artificial intelligence,Pixel,Wavelet transform
Conference
Volume
Issue
ISSN
2007
1
1063-6919 E-ISBN : 1-4244-1180-7
ISBN
Citations 
PageRank 
1-4244-1180-7
19
0.83
References 
Authors
9
7
Name
Order
Citations
PageRank
Nedeljko Cvejic1190.83
Stavri G. Nikolov224612.64
Henry D. Knowles3343.20
Artur Łoza41409.92
Alin Achim569961.36
David R. Bull61736189.86
Cedric Nishan Canagarajah715418.85