By Topic

Segmentation methods for visual tracking of deep-ocean jellyfish using a conventional camera

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
J. Rife ; Stanford Univ., CA, USA ; S. M. Rock

This paper presents a vision algorithm that enables automated jellyfish tracking using remotely operated vehicles (ROVs) or autonomous underwater vehicles (AUVs). The discussion focuses on algorithm design. The introduction provides a novel performance-assessment tool, called segmentation efficiency, which aids in matching potential vision algorithms to the jelly-tracking task. This general-purpose tool evaluates the inherent applicability of various algorithms to particular tracking applications. This tool is applied to the problem of tracking transparent jellyfish under uneven time-varying illumination in particle-filled scenes. The result is the selection of a fixed-gradient threshold-based vision algorithm. This approach, implemented as part of a pilot aid for the Monterey Bay Aquarium Research Institute's ROV Ventana, has demonstrated automated jelly tracking for as long as 89 min.

Published in:

IEEE Journal of Oceanic Engineering  (Volume:28 ,  Issue: 4 )