Beaulieu, Stace E

Fornari, D J

Mayer, Larry A.

Rzhanov, Yuri

Shank, Tim M

Soule, Adam

English

UNH Scholars' Repository

University of New HampshireUniversity of New Hampshire Scholars' RepositoryCenter for Coastal and Ocean Mapping Center for Coastal and Ocean Mapping2006Automated generation of geo-referenced mosaicsfrom video collected by deep submergencevehicles: an example from Rosebud vent(Galapagos Rift)Stace E. BeaulieuWoods Hole Oceanographic InstitutionTim M. ShankWoods Hole Oceanographic InstitutionAdam SouleWoods Hole Oceanographic InstitutionD J. FornariWoods Hole Oceanographic Inst.Yuri RzhanovUniversity of New Hampshire, Durham, Yuri.Rzhanov@unh.eduSee next page for additional authorsFollow this and additional works at: https://scholars.unh.edu/ccomPart of the Oceanography and Atmospheric Sciences and Meteorology CommonsThis Poster is brought to you for free and open access by the Center for Coastal and Ocean Mapping at University of New Hampshire Scholars'Repository. It has been accepted for inclusion in Center for Coastal and Ocean Mapping by an authorized administrator of University of NewHampshire Scholars' Repository. For more information, please contact nicole.hentz@unh.edu.Recommended CitationBeaulieu, Stace E.; Shank, Tim M.; Soule, Adam; Fornari, D J.; Rzhanov, Yuri; and Mayer, Larry A., "Automated generation of geo-referenced mosaics from video collected by deep submergence vehicles: an example from Rosebud vent (Galapagos Rift)" (2006).Deep-Sea Biology Symposium (DSBS). 579.https://scholars.unh.edu/ccom/579AuthorsStace E. Beaulieu, Tim M. Shank, Adam Soule, D J. Fornari, Yuri Rzhanov, and Larry A. MayerThis poster is available at University of New Hampshire Scholars' Repository: https://scholars.unh.edu/ccom/579Automated generation of geo-referenced mosaics from video collected by deep-submergence vehicles: an example from Rosebud Vent (Galapagos Rift) Stace Beaulieu (stace@whoi.edu), Adam Soule, Tim Shank, & Dan FornariWoods Hole Oceanographic Institution, Woods Hole, MA, 02543 USAYuri Rzhanov & Larry MayerCenter for Coastal and Ocean Mapping, Univ. of New Hampshire, Durham, NH, 03824 USA1234Automated video mosaic vs. manual still mosaicMosaicking basicsObjectivesFig. 7. Video mosaics for Marker B siteat Rosebud in 2002 (top) and 2005 (bottom).ResultsMethodsStudy siteRegistration and geo-referencing  procedureMosaic placement into GISFig. 6.  Video segment in GIS0˚48’21”N86˚13’39”W0 10 20 30 40MetersActive ventsDive 41172m contourCamera TowAT11-27 AlvinRosebud    mbsl-2448-245317:34:4917:35:52Conclusions and future goalsGIS may be used to display the mosaics andassociated metadata.  Transect mosaics maybe displayed in association with vehicle track lines.Fig. 2. Minimum overlap for automated processingAssuming camera normal to seafloor and lens angle 40 ,the field of view in direction of travel is approx. 3/4 x altitude.At 4m altitude, moving 1/2kt (approx. 25 cm/s), need 1 frameevery 4 sec.  At 6m altitude, need 1 frame every 6 sec.0Directionof travelAltitude6 m4 m2/3 overlapGalapagos ArchipelagoW. GSCE. GSCFig. 1. Study site (  ) for images and data on this poster (Eastern Galapagos Spreading Center, 1 N, 86 W)00Fig. 4.Output of co-registration, indicating(A) frame numbers, (B) overlap %,and (C) satisfactory matches.A CBMany advances in understanding biological processes at the deep seafloor are facilitatedby direct observation.  Mosaics of seafloor imagery have significant advantages over stillphotographs and video because they are able to capture large areas while retainingsufficient resolution to identify small-scale features.  During a typical submersible or ROVdive, hours of video are recorded.  Our objective is to develop user-friendly software tomosaic this video, allowing researchers to create “photographic dive tracks”.Our software is tailored for the incorporation of video mosaics into GIS quickly followinga dive.  “Photographic dive tracks” can be used for dive planning during a cruiseand can be used for “legacy” video of past cruises for time-series comparisons.Here, we present initial results of our project to automatethe creation of geo-referenced seafloor mosaics from videoand navigation data.  During a cruise to the Galapagos Riftin May 2005, we utilized our software with data from thesubmersible Alvin to mosaic the seafloor at Rosebud Vent.Mosaicking involves the co-registration of frameswith overlapping features (determining thetransformation relating pixels of two images).The main assumption for mosaic constructionis that the imaged surface is flat, which isoften violated in the rough topography ofmid-ocean ridges.  Distortions lead to anaccumulation of co-registration error overa sequence of images.We co-register images utilizing a 4-parameter rigid affine model.  This model captures rotation, translation, and scaling.  Our mosaicking technique involves the featureless Fourier domain method in conjunction with artificial intelligence (Support Vector Machine) for transformation quality assessment, allowing an automated co-registration process.Fig. 3. Stages in automated processingThe following protocol assumes that video frames are time-tagged and that navigationdata are recorded frequently (e.g. LBL positions renavigated with Doppler navigation).  (1) Use vehicle navigation data (position and altitude) to determine      segments of overlapping frames from an entire dive.(2) Extract frames directly from DVCAM tapes.(3) Process frames, co-register, and verify with navigation.(4) Construct geo-referenced mosaic (world file and/or GeoTIFF).Fig. 5.  Transect mosaics with contrast-enhanced frames.  10-min sequence from Alvin Dive 4117.Arrows indicate matching features.  The seven video segments will overlay when placed into GIS.The initial frame of each segment is tied to vehicle position and heading.Video segmentsDown-looking, strobed still cameraMarker NMarker LStill camera mosaic constructed manually due to low overlap.AcknowledgmentsWe would like to thank the crew of R/V Atlantis and the Alvin group.  CruiseAT11-27 was funded by NOAA Ocean Exploration Grant #NA04OAR460084.Our video mosaicking work is funded by NSF Grants #0452528 and #0451983.Suggestions for usersWe are now poised to use our software to generate geo-referenced mosaics of the seafloor at Rosebud from “legacy video”, to quantify the temporal changes in vent community distribution.  On our next cruise, in Oct. 2006, we will test our software during Alvin dives at the East Pacific Rise.For validation of the automated processing, we compared video mosaic segments to manually-constructed still camera mosaics.Mosaicking during a dive involves a compromisebetween altitude, speed, camera positioning, andlighting.  Overall, the best mosaicking is likely toderive from a dedicated camera/lighting system.Video mosaicking as described here allows formaximum use of existing video cameras on Alvin.To lower the accumulated co-registration error and work with a manageable imagesize, our software divides video transects into ~15-m segments for mosaicking. Nav_processTapeAcquireSegments_ProcessMosaic_Process~15 mMarker AMarker B

Automated generation of geo-referenced mosaics from video collected by deep submergence vehicles: an example from Rosebud vent (Galapagos Rift)

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Automated generation of geo-referenced mosaics from video collected by deep submergence vehicles: an example from Rosebud vent (Galapagos Rift)

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