@article{426d87607ef043f9aa4c828eafa28c06,
title = "SHREC{\textquoteright}20 Track: Retrieval of digital surfaces with similar geometric reliefs",
abstract = "This paper presents the methods that have participated in the SHREC{\textquoteright}20 contest on retrieval of surface patches with similar geometric reliefs and the analysis of their performance over the benchmark created for this challenge. The goal of the context is to verify the possibility of retrieving 3D models only based on the reliefs that are present on their surface and to compare methods that are suitable for this task. This problem is related to many real world applications, such as the classification of cultural heritage goods or the analysis of different materials. To address this challenge, it is necessary to characterize the local ”geometric pattern” information, possibly forgetting model size and bending. Seven groups participated in this contest and twenty runs were submitted for evaluation. The performances of the methods reveal that good results are achieved with a number of techniques that use different approaches.",
keywords = "3D Models, Contest, Reliefs retrieval",
author = "\{Moscoso Thompson\}, Elia and Silvia Biasotti and Andrea Giachetti and Claudio Tortorici and Naoufel Werghi and Obeid, \{Ahmad Shaker\} and Stefano Berretti and Nguyen-Dinh, \{Hoang Phuc\} and Le, \{Minh Quan\} and Nguyen, \{Hai Dang\} and Tran, \{Minh Triet\} and Leonardo Gigli and Santiago Velasco-Forero and Beatriz Marcotegui and Ivan Sipiran and Benjamin Bustos and Ioannis Romanelis and Vlassis Fotis and Gerasimos Arvanitis and Konstantinos Moustakas and Ekpo Otu and Reyer Zwiggelaar and David Hunter and Yonghuai Liu and Yoko Arteaga and Ramamoorthy Luxman",
note = "Funding Information: The authors thank the 3DOR 2020 Workshop and Program Chairs for helping us in the organization of our contest despite the current COVID-19 pandemic. We also thank the anonymous reviewers for providing constructive comments on earlier drafts of the manuscript, which helped us to improve and clarify this work. This study was partially supported by the CNR-IMATI projects DIT.AD004.100 and DIT.AD021.080.001. Research for the team from University of Science, Ho Chi Minh city, Vietnam is supported by Vingroup Innovation Foundation (VINIF) in project code VINIF.2019.DA19. The team Y. Arteaga and R. Luxman research is funded by the Horizon 2020 programme of the European Union Grant \#813789. The work of Ivan Sipiran has been supported by Proyecto de Mejoramiento y Ampliacin de los Servicios del Sistema Nacional de Ciencia Tecnologȡa e Innovacin Tecnolgica(Banco Mundial, Concytec), Nro. grant 062-2018-FONDECYT-BM-IADT-AV. The work of Benjamin Bustos is funded by the Millennium Institute Foundational Research on Data (IMFD). Funding Information: This study was partially supported by the CNR-IMATI projects DIT.AD004.100 and DIT.AD021.080.001. Research for the team from University of Science, Ho Chi Minh city, Vietnam is supported by Vingroup Innovation Foundation (VINIF) in project code VINIF.2019.DA19. The team Y. Arteaga and R. Luxman research is funded by the Horizon 2020 programme of the European Union Grant . The work of Ivan Sipiran has been supported by Proyecto de Mejoramiento y Ampliacin de los Servicios del Sistema Nacional de Ciencia Tecnologȡa e Innovacin Tecnolgica(Banco Mundial, Concytec), Nro. grant 062-2018-FONDECYT-BM-IADT-AV. The work of Benjamin Bustos is funded by the Millennium Institute Foundational Research on Data (IMFD). Publisher Copyright: {\textcopyright} 2020 Elsevier Ltd",
year = "2020",
month = oct,
doi = "10.1016/j.cag.2020.07.011",
language = "British English",
volume = "91",
pages = "199--218",
journal = "Computers and Graphics (Pergamon)",
issn = "0097-8493",
publisher = "Elsevier Ltd",
}