Learning Higher-Order Markov Models for Object Tracking in Image Sequences-Reference-Cited by-同舟云学术

Learning Higher-Order Markov Models for Object Tracking in Image Sequences

Published:2009 Issue: Volume: Page:184-195
ISSN:0302-9743
Container-title:Advances in Visual Computing
language:
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Author:

Felsberg Michael,Larsson Fredrik

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-10520-3_17.pdf

Reference25 articles.

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2. Arulampalam, M.S., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans. Sig. P. 50, 174–188 (2002)

3. Isard, M., Blake, A.: CONDENSATION – conditional density propagation for visual tracking. International Journal of Computer Vision 29, 5–28 (1998)

4. Coué, C., Fraichard, T., Bessière, P., Mazer, E.: Using Bayesian programming for multi-sensor multitarget tracking in automotive applications. In: ICRA (2003)

5. Granlund, G.H.: An Associative Perception-Action Structure Using a Localized Space Variant Information Representation. In: Proceedings of the AFPAC Workshop (2000)

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