Detecting fish in underwater video using the EM algorithm
作者： F.H. Evans
DOI: 10.1109/ICIP.2003.1247423
关键词:
摘要: We consider the problem of detecting fish in underwater video. adopt a modeling framework, where shape each is assumed to be multivariate Gaussian. Mixture used classify noise and varying numbers fish. The mixture parameters are estimated using an EM algorithm that incorporates Akaike information criterion simultaneously estimate number components mixture. In addition, does not require careful initialization.
murdoch.edu.au参考文章(9)
Mark Shortis, David Fletcher, Euan Harvey, A comparison of the precision and accuracy of estimates of reef-fish lengths determined visually by divers with estimates produced by a stereo-video system. Fishery Bulletin. ,vol. 99, pp. 63- 71 ,(2001)
J. A. Bilmes, A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models CTIT technical reports series. ,(1998)
Robert Eugene Boyce, Simple scale determination on underwater stereo pairs Deep Sea Research and Oceanographic Abstracts. ,vol. 11, pp. 89- 91 ,(1964) , 10.1016/0011-7471(64)91085-X
Hamparsum Bozdogan, Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions Psychometrika. ,vol. 52, pp. 345- 370 ,(1987) , 10.1007/BF02294361
R.J. Petrell, X. Shi, R.K. Ward, A. Naiberg, C.R. Savage, Determining fish size and swimming speed in cages and tanks using simple video techniques Aquacultural Engineering. ,vol. 16, pp. 63- 84 ,(1997) , 10.1016/S0144-8609(96)01014-X
M.A.T. Figueiredo, A.K. Jain, Unsupervised learning of finite mixture models IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 24, pp. 381- 396 ,(2002) , 10.1109/34.990138
Toni A. Beddow, Lindsay G. Ross, John A. Marchant, Predicting salmon biomass remotely using a digital stereo-imaging technique Aquaculture. ,vol. 146, pp. 189- 203 ,(1996) , 10.1016/S0044-8486(96)01384-1
B.P. Ruff, J.A. Marchant, A.R. Frost, Fish sizing and monitoring using a stereo image analysis system applied to fish farming Aquacultural Engineering. ,vol. 14, pp. 155- 173 ,(1995) , 10.1016/0144-8609(94)P4433-C
A. P. Dempster, N. M. Laird, D. B. Rubin, Maximum Likelihood from Incomplete Data Via theEMAlgorithm Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 39, pp. 1- 22 ,(1977) , 10.1111/J.2517-6161.1977.TB01600.X