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Guiding random particles by deterministic search

Abstract:

Among the algorithms developed towards the goal of robust and efficient tracking, two approaches which stand out due to their success are those based on particle filtering [8, 12, 14] and variational approaches [5, 16]. The Bayesian approach led to the development of the particle filter, which performs a random search guided by a stochastic motion model. On the other hand, localising an object can be based on minimising a cost function. This minimum can be found using variational methods. The...

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Role:
Author
Journal:
Proceedings of the IEEE International Conference on Computer Vision
Volume:
1
Pages:
323-330
Publication date:
2001-01-01
Source identifiers:
439076
Language:
English
Pubs id:
pubs:439076
UUID:
uuid:00ecda38-a2ff-4af5-a0c8-b53d083ca891
Local pid:
pubs:439076
Deposit date:
2014-02-08

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