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 :
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