SHREC 2020 track: River gravel characterization

A. Giachetti, S. Biasotti, E. Moscoso Thompson, L. Fraccarollo, Q. Nguyen, H. Nguyen, M. Tran, G. Arvanitis, I. Romanelis, V. Fotis, K. Moustakas, C. Tortorici, N. Werghi, S. Berretti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The quantitative analysis of the distribution of the different types of sands, gravels and cobbles shaping river beds is a very important task performed by hydrologists to derive useful information on fluvial dynamics and related processes (e.g., hydraulic resistance, sediment transport and erosion, habitat suitability. As the methods currently employed in the practice to perform this evaluation are expensive and time-consuming, the development of fast and accurate methods able to provide a reasonable estimate of the gravel distribution based on images or 3D scanning data would be extremely useful to support hydrologists in their work. To evaluate the suitability of state-of-the-art geometry processing tool to estimate the distribution from digital surface data, we created, therefore, a dataset including real captures of riverbed mockups, designed a retrieval task on it and proposed them as a challenge of the 3D Shape Retrieval Contest (SHREC) 2020. In this paper, we discuss the results obtained by the methods proposed by the groups participating in the contest and baseline methods provided by the organizers. Retrieval methods have been compared using the precision-recall curves, nearest neighbor, first tier, second tier, normalized discounted cumulated gain and average dynamic recall. Results show the feasibility of gravels characterization from captured surfaces and issues in the discrimination of mixture of gravels of different size.

Original languageBritish English
Title of host publicationEG 3DOR 2020 - Eurographics Workshop on 3D Object Retrieval, Short Papers
EditorsTobias Schreck, Theoharis Theoharis, Theoharis Theoharis, Ioannis Pratikakis, Michela Spagnuolo, Remco Veltkamp, Dieter W. Fellner, Werner Hansmann, Werner Purgathofer, Francois Sillion
Pages27-35
Number of pages9
ISBN (Electronic)9783038681267
DOIs
StatePublished - 2020
Event2020 Eurographics Workshop on 3D Object Retrieval, EG 3DOR 2020 - Graz, Austria
Duration: 4 Sep 20205 Sep 2020

Publication series

NameEurographics Workshop on 3D Object Retrieval, EG 3DOR
Volume2020-September
ISSN (Print)1997-0463
ISSN (Electronic)1997-0471

Conference

Conference2020 Eurographics Workshop on 3D Object Retrieval, EG 3DOR 2020
Country/TerritoryAustria
CityGraz
Period4/09/205/09/20

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