%A Schoening,Timm %A Kuhn,Thomas %A Bergmann,Melanie %A Nattkemper,Tim W. %D 2015 %J Frontiers in Marine Science %C %F %G English %K Laser point detection,Image Footprint Quantification,Arbitrary Image Collections,Web-based Image Annotation,Annotation Enhancement,Marine Imaging,Underwater image analysis,Remote Sensing Technology,image processing,pattern recognition,Intelligent systems,computational learning %Q %R 10.3389/fmars.2015.00020 %W %L %M %P %7 %8 2015-April-17 %9 Methods %+ Timm Schoening,Biodata Mining Group, Bielefeld University,Germany,tschoening@geomar.de %# %! DELPHI - Computational laser point detection and visual footprint quantification %* %< %T DELPHI—fast and adaptive computational laser point detection and visual footprint quantification for arbitrary underwater image collections %U https://www.frontiersin.org/articles/10.3389/fmars.2015.00020 %V 2 %0 JOURNAL ARTICLE %@ 2296-7745 %X Marine researchers continue to create large quantities of benthic images e.g., using AUVs (Autonomous Underwater Vehicles). In order to quantify the size of sessile objects in the images, a pixel-to-centimeter ratio is required for each image, often indirectly provided through a geometric laser point (LP) pattern, projected onto the seafloor. Manual annotation of these LPs in all images is too time-consuming and thus infeasible for nowadays data volumes. Because of the technical evolution of camera rigs, the LP's geometrical layout and color features vary for different expeditions and projects. This makes the application of one algorithm, tuned to a strictly defined LP pattern, also ineffective. Here we present the web-tool DELPHI, that efficiently learns the LP layout for one image transect/collection from just a small number of hand labeled LPs and applies this layout model to the rest of the data. The efficiency in adapting to new data allows to compute the LPs and the pixel-to-centimeter ratio fully automatic and with high accuracy. DELPHI is applied to two real-world examples and shows clear improvements regarding reduction of tuning effort for new LP patterns as well as increasing detection performance.