DocumentCode
3674388
Title
On fusion for robust motion segmentation
Author
Longzhen Li;Anna Ellis;James Ferryman
Author_Institution
Computational Vision Group, School of Systems Engineering, University of Reading, UK
fYear
2015
Firstpage
1
Lastpage
6
Abstract
While a multitude of motion segmentation algorithms have been presented in the literature, there has not been an objective assessment of different approaches to fusing their outputs. This paper investigates the application of 4 different fusion schemes to the outputs of 3 probabilistic pixel-level segmentation algorithms. We performed an extensive experimentation using 6 challenge categories from the changedetection.net dataset demonstrating that in general simple majority vote proves to be more effective than more complex fusion schemes.
Keywords
"Entropy","Bismuth"
Publisher
ieee
Conference_Titel
Advanced Video and Signal Based Surveillance (AVSS), 2015 12th IEEE International Conference on
Type
conf
DOI
10.1109/AVSS.2015.7301776
Filename
7301776
Link To Document