SHREC’14 Track: Retrieval and Classification on Textured 3D Models

نویسندگان

  • S. Biasotti
  • A. Cerri
  • M. Abdelrahman
  • M. Aono
  • A. Ben Hamza
  • M. El-Melegy
  • A. Farag
  • V. Garro
  • A. Giachetti
  • A. Godil
  • C. Li
  • Y.-J. Liu
  • H. Y. Martono
  • C. Sanada
  • A. Tatsuma
  • S. Velasco-Forero
  • C.-X. Xu
چکیده

This paper reports the results of the SHREC’14 track: Retrieval and classification on textured 3D models, whose goal is to evaluate the performance of retrieval algorithms when models vary either by geometric shape or texture, or both. The collection to search in is made of 572 textured mesh models, having a two-level classification based on geometry and texture. Together with the dataset, a training set of 96 models was provided. The track saw eight participants and the submission of 22 runs, to either the retrieval or the classification contest, or both. The evaluation results show a promising scenario about textured 3D retrieval methods, and reveal interesting insights in dealing with texture information in the CIELab rather than in the RGB colour space.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

SHREC'13 Track: Retrieval on Textured 3D Models

This contribution reports the results of the SHREC 2013 track: Retrieval on Textured 3D Models, whose goal is to evaluate the performance of retrieval algorithms when models vary either by geometric shape or texture, or both. The collection to search in is made of 240 textured mesh models, divided into 10 classes. Each model has been used in turn as a query against the remaining part of the dat...

متن کامل

New Composite Shape and Texture Descriptors for 3D Model Retrieval

Nowadays, problem of shape and texture for 3D retrieval is still a challenge research. Although several methods exist, but we still have a space to improve the performance. In this paper, we aim to improve our previous 3D shape features and inserting texture features. We first do pose normalization as a process of adjusting the size, location, and orientation of a given object in a canonical sp...

متن کامل

Retrieval of Non-rigid (textured) Shapes Using Low Quality 3D Models

This paper reports the results of the SHREC 2015 track on retrieval of non-rigid (textured) shapes from low quality 3D models. This track has been organized to test the ability of the algorithms recently proposed by researchers for the retrieval of articulated and textured shapes to deal with real-world deformations and acquisition noise. For this reason we acquired with low cost devices models...

متن کامل

SHREC 2009 - Shape Retrieval Contest

The general objective of the 3D Shape Retrieval Contest (see http://www.aimatshape.net/event/ SHREC) is to evaluate the effectiveness of 3D-shape retrieval algorithms. After three years of success, the contest is now organized in conjunction with the Eurographics Workshop on 3D Object Retrieval, where the evaluation results are presented. Thanks to the effort of previous track organizers, SHREC...

متن کامل

SHREC'10 Track: Protein Model Classification

This paper presents the results of the 3D Shape Retrieval Contest 2010 (SHREC’10) track Protein Models Classification. The aim of this track is to evaluate how well 3D shape recognition algorithms can classify protein structures according to the CATH [CSL∗08] superfamily classification. Five groups participated in this track, using a total of six methods, and for each method a set of ranked pre...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014