Markerless tracking algorithm based on 3D model for augmented reality system

Peng Yao; Can Chen; Dongdong Weng

doi:10.1007/978-3-642-36669-7_91

Markerless tracking algorithm based on 3D model for augmented reality system

Peng Yao
, Can Chen
, Dongdong Weng

光电学院

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

We present a markerless augmented reality(AR) system based on 3D model. First, the feature of environment was extracted using SIFT operator, then the method of stratified reconstruction was used to reconstruct the 3D scene, after that we constructed the database of prior knowledge using the KDTree. Finally, we tracked the 3D model based on these prior knowledge via feature matching and pose estimation in real time. Experimental results demonstrated that this method is sufficient for markerless tracking registration. With the prior knowledge, key frame selection problem can be avoided and the running speed is also increased.

源语言	英语
主期刊名	Intelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers
页	751-758
页数	8
DOI	https://doi.org/10.1007/978-3-642-36669-7_91
出版状态	已出版 - 2013
活动	3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012 - Nanjing, 中国期限: 15 10月 2012 → 17 10月 2012

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	7751 LNCS
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012
国家/地区	中国
市	Nanjing
时期	15/10/12 → 17/10/12

访问文件

10.1007/978-3-642-36669-7_91

其它文件与链接

链接到 Scopus 的出版物

引用此

Yao, P., Chen, C., & Weng, D. (2013). Markerless tracking algorithm based on 3D model for augmented reality system. 在 Intelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers (页码 751-758). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 7751 LNCS). https://doi.org/10.1007/978-3-642-36669-7_91

Yao, Peng ; Chen, Can ; Weng, Dongdong. / Markerless tracking algorithm based on 3D model for augmented reality system. Intelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers. 2013. 页码 751-758 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{1725b4a0609f4903a9c160ac00f4fd1c,

title = "Markerless tracking algorithm based on 3D model for augmented reality system",

abstract = "We present a markerless augmented reality(AR) system based on 3D model. First, the feature of environment was extracted using SIFT operator, then the method of stratified reconstruction was used to reconstruct the 3D scene, after that we constructed the database of prior knowledge using the KDTree. Finally, we tracked the 3D model based on these prior knowledge via feature matching and pose estimation in real time. Experimental results demonstrated that this method is sufficient for markerless tracking registration. With the prior knowledge, key frame selection problem can be avoided and the running speed is also increased.",

author = "Peng Yao and Can Chen and Dongdong Weng",

year = "2013",

doi = "10.1007/978-3-642-36669-7\_91",

language = "English",

isbn = "9783642366680",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "751--758",

booktitle = "Intelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers",

note = "3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012 ; Conference date: 15-10-2012 Through 17-10-2012",

}

Yao, P, Chen, C & Weng, D 2013, Markerless tracking algorithm based on 3D model for augmented reality system. 在 Intelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 7751 LNCS, 页码 751-758, 3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012, Nanjing, 中国, 15/10/12. https://doi.org/10.1007/978-3-642-36669-7_91

Markerless tracking algorithm based on 3D model for augmented reality system. / Yao, Peng; Chen, Can; Weng, Dongdong.
Intelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers. 2013. 页码 751-758 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 7751 LNCS).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Markerless tracking algorithm based on 3D model for augmented reality system

AU - Yao, Peng

AU - Chen, Can

AU - Weng, Dongdong

PY - 2013

Y1 - 2013

N2 - We present a markerless augmented reality(AR) system based on 3D model. First, the feature of environment was extracted using SIFT operator, then the method of stratified reconstruction was used to reconstruct the 3D scene, after that we constructed the database of prior knowledge using the KDTree. Finally, we tracked the 3D model based on these prior knowledge via feature matching and pose estimation in real time. Experimental results demonstrated that this method is sufficient for markerless tracking registration. With the prior knowledge, key frame selection problem can be avoided and the running speed is also increased.

AB - We present a markerless augmented reality(AR) system based on 3D model. First, the feature of environment was extracted using SIFT operator, then the method of stratified reconstruction was used to reconstruct the 3D scene, after that we constructed the database of prior knowledge using the KDTree. Finally, we tracked the 3D model based on these prior knowledge via feature matching and pose estimation in real time. Experimental results demonstrated that this method is sufficient for markerless tracking registration. With the prior knowledge, key frame selection problem can be avoided and the running speed is also increased.

UR - https://www.scopus.com/pages/publications/84892903129

U2 - 10.1007/978-3-642-36669-7_91

DO - 10.1007/978-3-642-36669-7_91

M3 - Conference contribution

AN - SCOPUS:84892903129

SN - 9783642366680

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 751

EP - 758

BT - Intelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers

T2 - 3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012

Y2 - 15 October 2012 through 17 October 2012

ER -

Yao P, Chen C, Weng D. Markerless tracking algorithm based on 3D model for augmented reality system. 在 Intelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers. 2013. 页码 751-758. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-36669-7_91

Markerless tracking algorithm based on 3D model for augmented reality system

摘要

出版系列

会议

访问文件

其它文件与链接

指纹

引用此