Current and future trends in marine image annotation software

Aguzzi, 2012, Challenges to the assessment of benthic populations and biodiversity as a result of rhythmic behaviour: video solutions from cabled observatories, Oceanogr. Mar. Biol. – Annu. Rev., 50, 235, 10.1201/b12157-6

Aguzzi, 2011, Automated image analysis for the detection of benthic crustaceans and bacterial mat coverage using the VENUS undersea cabled network, Sensors, 11, 10534, 10.3390/s111110534

Althaus, 2013

Bell, K.L.C., Brennan, M.L., Flanders, J., Raineault, N.A., Wagner, K. (Eds.), 2016. New Frontiers in Ocean Exploration: The E/V Nautilus and NOAA Ship Okeanos Explorer, 2015 Field Season.

Benoit-Bird, 2006, Extreme diel horizontal migrations by a tropical nearshore resident micronekton community, Mar. Ecol. Prog. Ser., 319, 1, 10.3354/meps319001

Beuck, 2016, Protocol for standardised underwater video analysis of European cold-water coral habitats with special emphasis on coral-fish interactions, Deep-Sea Res. II

Buneman, 2005

Burr, 2006, VACA: a tool for qualitative video analysis, 622

Cline, 2007, An automated visual event detection system for cabled observatory video

Costa, 2009, Colour calibration for quantitative biological analysis: a novel automated multivariate approach, Instrument. Viewpoint, 70

Costello, 2013, Global coordination and standardisation in marine biodiversity through the World Register of Marine Species (WoRMS) and related databases, PLoS ONE, 8, e51629, 10.1371/journal.pone.0051629

Cox, 1998, On the applications of multimedia processing to communications, Proc. IEEE, 86, 755, 10.1109/5.664272

Datta, 2005, Content-based image retrieval: approaches and trends of the new age, 253

Davies, 2016, A cold-water coral biota classification scheme for ecosystem-based management of the deep sea, Deep-Sea Res. II

Davies, 2004, 127

Dias, 2015, Area estimation of deep-sea surfaces from oblique still images, PLoS ONE, 10, 10.1371/journal.pone.0133290

Dunlop, 2015, An evaluation of deep-sea benthic megafauna length measurements obtained with laser and stereo camera methods, Deep Sea Res. Part I, 96, 38, 10.1016/j.dsr.2014.11.003

Edgington, 2006, Detecting, tracking and classifying animals in underwater video, 1

Edwards, 2000, Interoperability of biodiversity databases: biodiversity information on every desktop, Science, 289, 2312, 10.1126/science.289.5488.2312

Federal Geographic Data Committee (FGDC). 2012. FGDC-STD-018-2012. Coastal and marine ecological classification standard. Reston (VA): Federal Geographic Data Committee.

Gebali, 2014, Detection of salient events in large datasets of underwater video

Grassle, 2000, The Ocean Biogeographic Information System (OBIS): an on-line, worldwide atlas for accessing, modeling and mapping marine biological data in a multidimensional geographic context, Oceanography, 13, 5, 10.5670/oceanog.2000.01

Hagedorn, 2008, VCode and VData: illustrating a new framework for supporting the video annotation workflow, 317

Hauptmann, 2005, Lessons for the future from a decade of informedia video analysis research

Howell, 2014, Quality assurance in the identification of deep-sea taxa from video and image analysis: response to Henry and Roberts, ICES J. Mar. Sci.: J. Conseil, 71, 899, 10.1093/icesjms/fsu052

Huffard, 2016, Demographic indicators of change in a deposit- feeding abyssal holothurian community (Station M, 4000m), Deep-Sea Res. I: Oceanogr. Res. Papers, 109, 27, 10.1016/j.dsr.2016.01.002

Hudson, 2005, A review of the uses of work-class ROVs for the benefits of science: lessons learned from the SERPENT project, Underwater Technol., 26, 83, 10.3723/175605405784426637

INSPIRE, E., 2007, Directive: Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 Establishing an Infrastructure for Spatial Information in the European Community (INSPIRE), Off. J. Eur. Union, 108, 50

Itti, 2000, 1

Itti, 1998, A model of saliency-based visual attention for rapid scene analysis, IEEE Trans. Pattern Anal. Mach. Intell., 20, 1254, 10.1109/34.730558

Jaffe, 2001, Underwater optical imaging: status and prospects, Oceanography, 14, 66, 10.5670/oceanog.2001.24

Jamieson, 2013, Deep-sea benthic sampling, 285

Jones, 2009, The use of towed camera platforms in deep-water science, Underwater Technol., 28, 41, 10.3723/ut.28.041

Juniper, 2000, IRL: an interactive real-time, logging system for ROVs, 465

Kämpfe, 2004, AQUISAR: image retrieval in underwater webcam images

Kipp, 2001, ANVIL – a generic annotation tool for multimodal dialogue

Kitayama, 2012, Efficient management and promotion of utilization of the video information acquired by observation

Lerner, 2002

Leslie, 2010, Video acquisition, archiving, annotation and analysis: NEPTUNE Canada’s real-time georeferenced library of deep sea video, 1

Magurran, 2013, 179 pp

Mokhtarian, 2002, Shape similarity retrieval under affine transforms, Pattern Recogn., 35, 31, 10.1016/S0031-3203(01)00040-1

Morais, 2005, Particle filter-based predictive tracking for robust fish counting, 367

Morris, 2014, A new method for ecological surveying of the abyss using autonomous underwater vehicle photography, Limnol. Oceanogr.: Methods, 12, 795, 10.4319/lom.2014.12.795

Nattkemper, 2012, Are we ready for Science 2.0?

Ontrup, 2009, BIIGLE-Web 2.0 enabled labelling and exploring of images from the Arctic deep-sea observatory HAUSGARTEN, 1

Osterloff, 2016, A computer vision approach for monitoring the spatial and temporal shrimp distribution at the LoVe observatory, Methods Oceanogr., 15–16, 114, 10.1016/j.mio.2016.03.002

Pante, 2012, Getting to the point: accuracy of point count in monitoring ecosystem change, J. Mar. Biol., 2012, 10.1155/2012/802875

Pilgrim, 2000, ROV image scaling with laser spot patterns, Underwater Technol.: Int. J. Soc. Underwater, 24, 93, 10.3723/175605400783259684

Pinkard, 2005, Use of a video and laser system to quantify transect area for remotely operated vehicle (ROV) rockfish and abalone surveys, 2824

Porteiro, 2013, Distribution and habitat association of benthic fish on the Condor seamount (NE Atlantic, Azores) from in situ observations, Deep Sea Res. Part II, 98A, 114, 10.1016/j.dsr2.2013.09.015

Purser, 2009, Use of machine-learning algorithms for the automated detection of cold-water coral habitats: a pilot study, Mar. Ecol. Prog. Ser., 397, 241, 10.3354/meps08154

Rasenberg, 2011

2008

Rosenblum, 2004, Video-taped coding of working model of the child interviews: a viable and useful alternative to verbatim transcripts?, Infant Behav. Dev., 27, 544, 10.1016/j.infbeh.2004.04.001

Sameoto, J.A., Lawton, P., Strong, M.B., 2008. An Approach to the Development of a Relational Database and GIS Applicable Scheme for the Analysis of Video-Based Surveys of Benthic Habitats. Canadian Technical Report of Fisheries and Aquatic Sciences 2818: iv, 34 p.

Schlining, 2006, MBARI’s video annotation and reference system

Schneider, 2012, NIH Image to ImageJ: 25 years of image analysis, Nat. Methods, 9, 671, 10.1038/nmeth.2089

Schoening, 2009, BIIGLE Tools – a Web 2.0 approach for visual Bioimage database mining, 51

Schoening, 2012, Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN, PLoS ONE, 7, e38179, 10.1371/journal.pone.0038179

Schoening, 2015, DELPHI – fast and adaptive computational laser point detection and visual footprint quantification for arbitrary underwater image collections, Front. Mar. Sci., 10.3389/fmars.2015.00020

Schoening, 2015, Rapid image processing and classification in underwater exploration using advanced high performance computing

Schoening, 2016, RecoMIA-Recommendations for Marine Image Annotation: lessons learned and future directions, Front. Mar. Sci., 3, 59, 10.3389/fmars.2016.00059

Shneiderman, 2008, Science 2.0, Science, 319, 1349, 10.1126/science.1153539

Shortis, 2013, A review of techniques for the identification and measurement of fish in underwater stereo-video image sequences, SPIE Optical Metrology 2013, Int. Soc. Opt. Photon., 87910G

Smeaton, 2005, 11

Solan, 2003, Towards a greater understanding of pattern, scale and process in marine benthic systems: a picture is worth a thousand worms, J. Exp. Mar. Biol. Ecol., 285, 313, 10.1016/S0022-0981(02)00535-X

Spampinato, 2008, Detecting, tracking and counting fish in low quality unconstrained underwater videos, Visapp, 2008, 514

Spampinato, 2010, Automatic fish classification for underwater species behavior understanding, 45

Strachan, 1993, Recognition of fish species by colour and shape, Image Vis. Comput., 11, 2, 10.1016/0262-8856(93)90027-E

Tran, 2013

Vevers, 1951, Photography of the sea floor, J. Mar. Biol. Assoc. United Kingdom, 30

Vondrick, 2013, Efficiently Scaling up Crowdsourced Video Annotation, Int. J. Comput. Vis., 101, 184, 10.1007/s11263-012-0564-1

Waldrop, 2008, Science 2.0: Great New Tool, or Great Risk? Wikis, blogs and other collaborative web technologies could usher in a new era of science Or not, Sci. Am., 10.1038/scientificamerican0508-68

Wakefield, 1987, The use of a Canadian (perspective) grid in deep-sea photography, Deep Sea Res. A: Oceanogr. Res. Papers, 34, 469, 10.1016/0198-0149(87)90148-8

Zhang, 2012, A review on automatic image annotation techniques, Pattern Recogn., 45, 346, 10.1016/j.patcog.2011.05.013