DocumentCode
1620234
Title
An automated event detection and classification system for abyssal time-series images of Station M, NE Pacific
Author
Cline, Danelle E. ; Edgington, Duane R. ; Smith, Ken L. ; Vardaro, Michael F. ; Kuhnz, Linda ; Ellena, Jacob A.
Author_Institution
Monterey Bay Aquarium Res. Inst., Moss Landing, CA, USA
fYear
2009
Firstpage
1
Lastpage
4
Abstract
The time-study data collected at the Station M site off the coast of central California includes high quality still-frame images taken in 1-hour time-lapse increments. The approximately 67,000 time-lapse images collected would take an unfeasible amount of time to fully analyze manually, and therefore would benefit from automated analysis. Towards this end, this work is an aid in the significant effort to analyze megafaunal activity and sedimentation events using an adapted version of the Automated Video Event Detection and Classification System (AVEDac) formerly designed by MBARI to analyze video collected from MBARI´s remotely operated underwater vehicles (ROVs) video. This paper describes, in general, the automated system that will aid in the abundance and distribution studies of animals at the Station M site.
Keywords
geophysical image processing; image classification; oceanographic equipment; oceanographic techniques; oceanography; remotely operated vehicles; sedimentation; time series; underwater vehicles; AVEDac; Automated Video Event Detection and Classification System; MBARI; NE Pacific; Station M site; abyssal time-series images; automated event detection; central California coast; event classification system; megafaunal activity; remotely operated underwater vehicles; sedimentation events; Animals; Application software; Biology computing; Cameras; Event detection; Image analysis; Jacobian matrices; Oceans; Remotely operated vehicles; XML;
fLanguage
English
Publisher
ieee
Conference_Titel
OCEANS 2009, MTS/IEEE Biloxi - Marine Technology for Our Future: Global and Local Challenges
Conference_Location
Biloxi, MS
Print_ISBN
978-1-4244-4960-6
Electronic_ISBN
978-0-933957-38-1
Type
conf
Filename
5422292
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