Change search
ReferencesLink to record
Permanent link

Direct link
Guiding Random Samples by Deterministic Search
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
2001 (English)Conference paper (Refereed)
Abstract [en]

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 and variational approaches. 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 search paradigms differ in these two methods. One is stochastic and model-driven while the other is deterministic and data-driven. This paper presents a new algorithm to incorporate the strengths of both approaches into one consistent framework. To allow this fusion a smooth, wide likelihood function is constructed, based on a sum-of-squares distance measure and an appropriate sampling scheme is introduced. Based on low-level information this scheme automatically mixes the two methods of search and adapts the computational demands of the algorithm to the difficulty of the problem at hand. The ability to effectively track complex motions without the need for finely tuned motion models is demonstrated

Place, publisher, year, edition, pages
2001. 323-330 p.
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-69632DOI: 10.1109/ICCV.2001.937536OAI: diva2:485656
Proceedings of the International Conference on Computer Vision
NR 20140805Available from: 2012-01-29 Created: 2012-01-29Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Sullivan, Josephine
By organisation
Computer Vision and Active Perception, CVAP
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 5 hits
ReferencesLink to record
Permanent link

Direct link