You are not logged in.
Openly accessible

Incremental learning of temporally-coherent gaussian mixture models

Arandjelovic, Ognjen and Cipolla, R. 2005, Incremental learning of temporally-coherent gaussian mixture models, in BMVC 2005 : Proceedings of the British Machine Conference 2005, BMVA Press, Manchester, England, pp. 59-1 (759)-59-10 (768), doi: 10.5244/C.19.59.

Attached Files
Name Description MIMEType Size Downloads
arandjelovic-incrementallearning-2005.pdf Published version application/pdf 503.38KB 32

Title Incremental learning of temporally-coherent gaussian mixture models
Author(s) Arandjelovic, Ognjen
Cipolla, R.
Conference name British Machine Vision. Conference (2005 : Oxford, England)
Conference location Oxford, England
Conference dates 5-8Sept. 2005
Title of proceedings BMVC 2005 : Proceedings of the British Machine Conference 2005
Editor(s) Clocksin, W F
Fitzgibbon, A W
Torr, P H S
Publication date 2005
Conference series British Machine Vision Conference
Start page 59-1 (759)
End page 59-10 (768)
Publisher BMVA Press
Place of publication Manchester, England
Summary In this paper we address the problem of learning Gaussian Mixture Models (GMMs) incrementally. Unlike previous approaches which universally assume that new data comes in blocks representable by GMMs which are then merged with the current model estimate, our method works for the case when novel data points arrive oneby- one, while requiring little additional memory. We keep only two GMMs in the memory and no historical data. The current fit is updated with the assumption that the number of components is fixed, which is increased (or reduced) when enough evidence for a new component is seen. This is deduced from the change from the oldest fit of the same complexity, termed the Historical GMM, the concept of which is central to our method. The performance of the proposed method is demonstrated qualitatively and quantitatively on several synthetic data sets and video sequences of faces acquired in realistic imaging conditions
ISBN 01901725294
Language eng
DOI 10.5244/C.19.59
Field of Research 080104 Computer Vision
080106 Image Processing
080109 Pattern Recognition and Data Mining
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2005, BMVA
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30058443

Document type: Conference Paper
Collections: Centre for Pattern Recognition and Data Analytics
Open Access Collection
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 82 Abstract Views, 32 File Downloads  -  Detailed Statistics
Created: Tue, 26 Nov 2013, 12:54:34 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.