SHREC 2024: Recognition of dynamic hand motions molding clay

IF 2.5 4区 计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING Computers & Graphics-Uk Pub Date : 2024-07-14 DOI:10.1016/j.cag.2024.104012
Ben Veldhuijzen , Remco C. Veltkamp , Omar Ikne , Benjamin Allaert , Hazem Wannous , Marco Emporio , Andrea Giachetti , Joseph J. LaViola Jr. , Ruiwen He , Halim Benhabiles , Adnane Cabani , Anthony Fleury , Karim Hammoudi , Konstantinos Gavalas , Christoforos Vlachos , Athanasios Papanikolaou , Ioannis Romanelis , Vlassis Fotis , Gerasimos Arvanitis , Konstantinos Moustakas , Christoph von Tycowicz
{"title":"SHREC 2024: Recognition of dynamic hand motions molding clay","authors":"Ben Veldhuijzen ,&nbsp;Remco C. Veltkamp ,&nbsp;Omar Ikne ,&nbsp;Benjamin Allaert ,&nbsp;Hazem Wannous ,&nbsp;Marco Emporio ,&nbsp;Andrea Giachetti ,&nbsp;Joseph J. LaViola Jr. ,&nbsp;Ruiwen He ,&nbsp;Halim Benhabiles ,&nbsp;Adnane Cabani ,&nbsp;Anthony Fleury ,&nbsp;Karim Hammoudi ,&nbsp;Konstantinos Gavalas ,&nbsp;Christoforos Vlachos ,&nbsp;Athanasios Papanikolaou ,&nbsp;Ioannis Romanelis ,&nbsp;Vlassis Fotis ,&nbsp;Gerasimos Arvanitis ,&nbsp;Konstantinos Moustakas ,&nbsp;Christoph von Tycowicz","doi":"10.1016/j.cag.2024.104012","DOIUrl":null,"url":null,"abstract":"<div><p>Gesture recognition is a tool to enable novel interactions with different techniques and applications, like Mixed Reality and Virtual Reality environments. With all the recent advancements in gesture recognition from skeletal data, it is still unclear how well state-of-the-art techniques perform in a scenario using precise motions with two hands. This paper presents the results of the SHREC 2024 contest organized to evaluate methods for their recognition of highly similar hand motions using the skeletal spatial coordinate data of both hands. The task is the recognition of 7 motion classes given their spatial coordinates in a frame-by-frame motion. The skeletal data has been captured using a Vicon system and pre-processed into a coordinate system using Blender and Vicon Shogun Post. We created a small, novel dataset with a high variety of durations in frames. This paper shows the results of the contest, showing the techniques created by the 5 research groups on this challenging task and comparing them to our baseline method.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"123 ","pages":"Article 104012"},"PeriodicalIF":2.5000,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S009784932400147X/pdfft?md5=d75274a315e451ba3701d800635d5155&pid=1-s2.0-S009784932400147X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Graphics-Uk","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S009784932400147X","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0

Abstract

Gesture recognition is a tool to enable novel interactions with different techniques and applications, like Mixed Reality and Virtual Reality environments. With all the recent advancements in gesture recognition from skeletal data, it is still unclear how well state-of-the-art techniques perform in a scenario using precise motions with two hands. This paper presents the results of the SHREC 2024 contest organized to evaluate methods for their recognition of highly similar hand motions using the skeletal spatial coordinate data of both hands. The task is the recognition of 7 motion classes given their spatial coordinates in a frame-by-frame motion. The skeletal data has been captured using a Vicon system and pre-processed into a coordinate system using Blender and Vicon Shogun Post. We created a small, novel dataset with a high variety of durations in frames. This paper shows the results of the contest, showing the techniques created by the 5 research groups on this challenging task and comparing them to our baseline method.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
SHREC 2024:识别粘土成型的动态手部动作
手势识别是实现与不同技术和应用(如混合现实和虚拟现实环境)进行新型交互的一种工具。近年来,通过骨骼数据进行手势识别的技术不断进步,但目前仍不清楚最先进的技术在使用双手精确动作的场景中表现如何。本文介绍了 SHREC 2024 竞赛的结果,该竞赛旨在评估使用双手骨骼空间坐标数据识别高度相似的手部动作的方法。任务是根据逐帧运动中的空间坐标识别 7 个运动类别。骨骼数据使用 Vicon 系统采集,并通过 Blender 和 Vicon Shogun Post 预处理成坐标系。我们创建了一个小型、新颖的数据集,其中的帧持续时间种类繁多。本文展示了竞赛的结果,展示了 5 个研究小组在这一具有挑战性的任务中创造的技术,并将它们与我们的基准方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Computers & Graphics-Uk
Computers & Graphics-Uk 工程技术-计算机:软件工程
CiteScore
5.30
自引率
12.00%
发文量
173
审稿时长
38 days
期刊介绍: Computers & Graphics is dedicated to disseminate information on research and applications of computer graphics (CG) techniques. The journal encourages articles on: 1. Research and applications of interactive computer graphics. We are particularly interested in novel interaction techniques and applications of CG to problem domains. 2. State-of-the-art papers on late-breaking, cutting-edge research on CG. 3. Information on innovative uses of graphics principles and technologies. 4. Tutorial papers on both teaching CG principles and innovative uses of CG in education.
期刊最新文献
Enhancing Visual Analytics systems with guidance: A task-driven methodology Learning geometric complexes for 3D shape classification RenalViz: Visual analysis of cohorts with chronic kidney disease Enhancing semantic mapping in text-to-image diffusion via Gather-and-Bind CGLight: An effective indoor illumination estimation method based on improved convmixer and GauGAN
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1