Automated registration for multi-year robotic surveys of marine benthic habitats
M. Bryson · M. Johnson-Roberson · O. Pizarro · Stefan B. Williams
TL;DR
Three automatic methods align seafloor survey maps taken up to two years apart, enabling long-term monitoring of reefs and kelp forests.
BRIEF
Tracking how coral reefs and kelp forests change requires comparing seafloor images taken months or years apart, and the maps must line up precisely. This work compares three automatic ways to align repeat survey maps built from underwater vehicle imagery. One matches image features across mosaics, one aligns the 3D seafloor shape recovered from the images, and one uses mutual information to cope with colour and brightness changes. The methods are tested on field data from sites along the Australian coast collected between 2009 and 2011.
Abstract
This paper presents recent developments in data processing of multi-year repeat survey imagery and precision automatic registration for monitoring long-term changes in benthic marine habitats such as coral reefs and kelp forests. Three different methods are presented and compared for precision alignment of imagery maps collected over a range of time-scales from 12 hours to two years between dives. The first method uses Scale Invariant Feature Transform (SIFT) features computed over imagery mosaics to compute the relative translational offset between repeat dives. The second method employs scan-optimisation using the bathymetry generated via structure-from-motion thus capturing more stable features in the environment, lending itself to larger timescale registration. The third method uses mutual information optimisation to register imagery maps, providing robustness to changes in the colour and brightness of objects in an underwater scene across multiple years. Results are presented from field data collected using an Autonomous Underwater Vehicle (AUV) in sites across the Australian coast between 2009 and 2011.