NDLI: A multiview, multimodal fusion framework for classifying small marine animals with an opto-acoustic imaging system

Content Provider	IEEE Xplore Digital Library
Author	Roberts, P.L.D. Jaffe, J.S. Trivedi, M.M.
Copyright Year	2009
Description	Author affiliation: Marine Physical Laboratory, Scripps Institution of Oceanography, 9500 Gilman Dr. La Jolla, CA 92093-0238, USA (Roberts, P.L.D.; Jaffe, J.S.) \|\| Electrical and Computer Engineering Department, University of California, San Diego, 9500 Gilman Dr. La Jolla, 29093-0434, USA (Trivedi, M.M.)
Abstract	A multiview, multimodal fusion algorithm for classifying marine plankton is described and its performance is evaluated on laboratory data from live animals. The algorithm uses support vector machines with softmax outputs to classify either acoustical or optical features. Outputs from these single-view classifiers are then combined together using a feedback network with confidence weighting. For each view or modality, the initial classification and classifications from all other views and modalities are confidence-weighted and combined to render a final, improved classification. Simple features are computed from acoustic and video data with an aim at noise robustness. The algorithm is tested on acoustic and video data collected in the laboratory from live, untethered copepods and mysids (two dominant crustacean zooplankton). It is shown that the algorithm is able to yield significant (≫ 50%) reductions in error by combining views together. In addition, it is shown that the algorithm is able boost performance by giving more weight to views or modalities that are more discriminant than others, without any a priori knowledge of which views are more discriminant.
Starting Page	1
Ending Page	6
File Size	659010
Page Count	6
File Format	PDF
ISBN	9781424454976
ISSN	15505790
e-ISBN	9781424454983
DOI	10.1109/WACV.2009.5403037
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Marine animals Laboratories Optical feedback Acoustic imaging Optical imaging Marine vegetation Support vector machines Support vector machine classification Output feedback Acoustic noise
Content Type	Text
Resource Type	Article

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