AR装配系统的指尖交互式跟踪配准方法

Yong Jiu, Wei Jianguo, Wang Yangping, Dang Jianwu, Lei Xiaomei
{"title":"AR装配系统的指尖交互式跟踪配准方法","authors":"Yong Jiu,&nbsp;Wei Jianguo,&nbsp;Wang Yangping,&nbsp;Dang Jianwu,&nbsp;Lei Xiaomei","doi":"10.1007/s43674-021-00025-5","DOIUrl":null,"url":null,"abstract":"<div><p>Aiming at the problems of single input mode and lack of naturalness in the assembly process of existing AR systems, a tracking registration method of mobile AR assembly system is proposed based on multi-quantity and multi-degree of freedom natural fingertip interaction. Firstly, the real-time and stable tracking of hand area in complex environment is realized based on the hand region tracking; secondly, the fingertip detection and recognition based on K-COS and parallel vector is used to improve the precision and stability of fingertip recognition; thirdly, the special movement track of fingertip is recognized based on improved DTW algorithm, which has strong compatibility and feature gradient transformation for complex fingertip trajectory recognition; finally, through the real-time transformation of projection relationship between fingertip and virtual object, the interaction between fingertip and virtual object is made more natural and realistic. The experimental results show that in the complex environment of background, illumination, scale and rotation, the precision of fingertip detection and recognition is about 93%, and the precision of fingertip motion template matching is about 91%. The translation error of the registration method based on visual feature recognition is reduced by about 100pix compared with fingertip tracking registration method, and the efficiency of mobile AR-guided assembly method is improved by about 24.77% compared with the traditional manual assisted assembly method. These data verifies the strong interaction and practicability of the fingertips based on the user's multi-quantity and multi-degree of freedom features in the process of mobile AR guided assembly.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43674-021-00025-5.pdf","citationCount":"2","resultStr":"{\"title\":\"Fingertip interactive tracking registration method for AR assembly system\",\"authors\":\"Yong Jiu,&nbsp;Wei Jianguo,&nbsp;Wang Yangping,&nbsp;Dang Jianwu,&nbsp;Lei Xiaomei\",\"doi\":\"10.1007/s43674-021-00025-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Aiming at the problems of single input mode and lack of naturalness in the assembly process of existing AR systems, a tracking registration method of mobile AR assembly system is proposed based on multi-quantity and multi-degree of freedom natural fingertip interaction. Firstly, the real-time and stable tracking of hand area in complex environment is realized based on the hand region tracking; secondly, the fingertip detection and recognition based on K-COS and parallel vector is used to improve the precision and stability of fingertip recognition; thirdly, the special movement track of fingertip is recognized based on improved DTW algorithm, which has strong compatibility and feature gradient transformation for complex fingertip trajectory recognition; finally, through the real-time transformation of projection relationship between fingertip and virtual object, the interaction between fingertip and virtual object is made more natural and realistic. The experimental results show that in the complex environment of background, illumination, scale and rotation, the precision of fingertip detection and recognition is about 93%, and the precision of fingertip motion template matching is about 91%. The translation error of the registration method based on visual feature recognition is reduced by about 100pix compared with fingertip tracking registration method, and the efficiency of mobile AR-guided assembly method is improved by about 24.77% compared with the traditional manual assisted assembly method. These data verifies the strong interaction and practicability of the fingertips based on the user's multi-quantity and multi-degree of freedom features in the process of mobile AR guided assembly.</p></div>\",\"PeriodicalId\":72089,\"journal\":{\"name\":\"Advances in computational intelligence\",\"volume\":\"2 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s43674-021-00025-5.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in computational intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s43674-021-00025-5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in computational intelligence","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s43674-021-00025-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

针对现有AR系统装配过程中输入模式单一、自然度不足的问题,提出了一种基于多量多自由度指尖自然交互的移动AR装配系统跟踪配准方法。首先,在手部区域跟踪的基础上,实现了复杂环境下手部区域的实时稳定跟踪;其次,采用基于K-COS和并行向量的指尖检测与识别方法,提高了指尖识别的精度和稳定性;再次,基于改进的DTW算法识别指尖的特殊运动轨迹,该算法对复杂指尖轨迹识别具有较强的兼容性和特征梯度变换;最后,通过对指尖与虚拟物体投影关系的实时转换,使指尖与虚拟对象的交互更加自然逼真。实验结果表明,在背景、光照、尺度和旋转的复杂环境下,指尖检测和识别的准确率约为93%,指尖运动模板匹配的准确度约为91%。与指尖跟踪配准方法相比,基于视觉特征识别的配准方法的平移误差降低了约100pix,移动AR引导装配方法的效率比传统的手动辅助装配方法提高了约24.77%。这些数据验证了在移动AR引导装配过程中,基于用户多数量、多自由度特征的指尖具有较强的交互性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Fingertip interactive tracking registration method for AR assembly system

Aiming at the problems of single input mode and lack of naturalness in the assembly process of existing AR systems, a tracking registration method of mobile AR assembly system is proposed based on multi-quantity and multi-degree of freedom natural fingertip interaction. Firstly, the real-time and stable tracking of hand area in complex environment is realized based on the hand region tracking; secondly, the fingertip detection and recognition based on K-COS and parallel vector is used to improve the precision and stability of fingertip recognition; thirdly, the special movement track of fingertip is recognized based on improved DTW algorithm, which has strong compatibility and feature gradient transformation for complex fingertip trajectory recognition; finally, through the real-time transformation of projection relationship between fingertip and virtual object, the interaction between fingertip and virtual object is made more natural and realistic. The experimental results show that in the complex environment of background, illumination, scale and rotation, the precision of fingertip detection and recognition is about 93%, and the precision of fingertip motion template matching is about 91%. The translation error of the registration method based on visual feature recognition is reduced by about 100pix compared with fingertip tracking registration method, and the efficiency of mobile AR-guided assembly method is improved by about 24.77% compared with the traditional manual assisted assembly method. These data verifies the strong interaction and practicability of the fingertips based on the user's multi-quantity and multi-degree of freedom features in the process of mobile AR guided assembly.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Non-linear machine learning with sample perturbation augments leukemia relapse prognostics from single-cell proteomics measurements ARBP: antibiotic-resistant bacteria propagation bio-inspired algorithm and its performance on benchmark functions Detection and classification of diabetic retinopathy based on ensemble learning Office real estate price index forecasts through Gaussian process regressions for ten major Chinese cities Systematic micro-breaks affect concentration during cognitive comparison tasks: quantitative and qualitative measurements
×
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