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Detecting fish in underwater video using the EM algorithm

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1 Author(s)
Evans, F.H. ; Sch. of Math. & Stat., Western Australia Univ., WA, Australia

We consider the problem of detecting fish in underwater video. We adopt a modeling framework, where the shape of each fish is assumed to be multivariate Gaussian. Mixture modeling is used to classify noise and varying numbers of fish. The mixture parameters are estimated using an EM algorithm that incorporates an Akaike information criterion to simultaneously estimate the number of components in the mixture. In addition, the algorithm does not require careful initialization.

Published in:

Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on  (Volume:3 )

Date of Conference:

14-17 Sept. 2003

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