Fish tracking by combining motion based segmentation and particle filtering

E. Bichot; L. Mascarilla; P. Courtellemont

doi:10.1117/12.650092

19 January 2006 Fish tracking by combining motion based segmentation and particle filtering

E. Bichot, L. Mascarilla, P. Courtellemont

Proceedings Volume 6077, Visual Communications and Image Processing 2006; 607728 (2006) https://doi.org/10.1117/12.650092
Event: Electronic Imaging 2006, 2006, San Jose, California, United States

Abstract

In this paper, we suggest a new importance sampling scheme to improve a particle filtering based tracking process. This scheme relies on exploitation of motion segmentation. More precisely, we propagate hypotheses from particle filtering to blobs of similar motion to target. Hence, search is driven toward regions of interest in the state space and prediction is more accurate. We also propose to exploit segmentation to update target model. Once the moving target has been identified, a representative model is learnt from its spatial support. We refer to this model in the correction step of the tracking process. The importance sampling scheme and the strategy to update target model improve the performance of particle filtering in complex situations of occlusions compared to a simple Bootstrap approach as shown by our experiments on real fish tank sequences.

Citation Download Citation

E. Bichot, L. Mascarilla, and P. Courtellemont "Fish tracking by combining motion based segmentation and particle filtering", Proc. SPIE 6077, Visual Communications and Image Processing 2006, 607728 (19 January 2006); https://doi.org/10.1117/12.650092

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available