On fusion for robust motion segmentation


Autoria(s): Li, Longzhen; Ellis, Anna; Ferryman, James
Data(s)

25/08/2015

Resumo

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.

Formato

text

Identificador

http://centaur.reading.ac.uk/48444/1/AVSS2015_FusionMotionSeg.pdf

Li, L. <http://centaur.reading.ac.uk/view/creators/90000503.html>, Ellis, A. <http://centaur.reading.ac.uk/view/creators/90000440.html> and Ferryman, J. <http://centaur.reading.ac.uk/view/creators/90000220.html> (2015) On fusion for robust motion segmentation. In: 12th IEEE International Conference on Advanced Video- and Signal-based Surveillance (AVSS2015), August 25-28, 2015, Karlsruhe, Germany, pp. 1-6.

Idioma(s)

en

Relação

http://centaur.reading.ac.uk/48444/

creatorInternal Li, Longzhen

creatorInternal Ellis, Anna

creatorInternal Ferryman, James

http://dx.doi.org/10.1109/AVSS.2015.7301776

Tipo

Conference or Workshop Item

PeerReviewed