Details
| Original language | English |
|---|---|
| Title of host publication | Optical Metrology and Inspection for Industrial Applications V |
| Editors | Toru Yoshizawa, Song Zhang, Sen Han, Sen Han |
| Publisher | SPIE |
| Number of pages | 13 |
| ISBN (electronic) | 9781510622364 |
| Publication status | Published - 2 Nov 2018 |
| Event | Optical Metrology and Inspection for Industrial Applications V 2018 - Beijing, China Duration: 11 Oct 2018 → 13 Oct 2018 |
Publication series
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Volume | 10819 |
| ISSN (Print) | 0277-786X |
| ISSN (electronic) | 1996-756X |
Abstract
This paper presents a novel visual tracking approach that combines the NMI metric and the traditional SSD metric within a gradient-based optimization frame, which can be used for direct visual odometry and SLAM. We firstly derivate the closed form expression for first- and second-order analytical NMI derivatives under the assumption of rigid-body transformations, which then can be used by subsequent Newton-like optimization methods. Then we develop a robust tracking scheme that utilizes the robustness of NMI metric while keeping the optimization characteristics of SSD-based Lucas-Kanade (LK) tracking methods. To validate the robustness and accuracy of the proposed approach, several experiments are performed on synthetic datasets as well as real image datasets. The experimental results demonstrate that our approach can provide fast, accurate pose estimation and obtain better tracking performance over standard SSD-based methods in most cases.
Keywords
- Direct visual tracking, Nonlinear optimization, Normalized mutual information, Sum of squared differences
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Physics and Astronomy(all)
- Condensed Matter Physics
- Computer Science(all)
- Computer Science Applications
- Mathematics(all)
- Applied Mathematics
- Engineering(all)
- Electrical and Electronic Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Optical Metrology and Inspection for Industrial Applications V. ed. / Toru Yoshizawa; Song Zhang; Sen Han; Sen Han. SPIE, 2018. 108190T (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10819).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Robust direct vision-based pose tracking using normalized mutual information
AU - Luo, Hang
AU - Pape, Christian
AU - Reithmeier, Eduard
PY - 2018/11/2
Y1 - 2018/11/2
N2 - This paper presents a novel visual tracking approach that combines the NMI metric and the traditional SSD metric within a gradient-based optimization frame, which can be used for direct visual odometry and SLAM. We firstly derivate the closed form expression for first- and second-order analytical NMI derivatives under the assumption of rigid-body transformations, which then can be used by subsequent Newton-like optimization methods. Then we develop a robust tracking scheme that utilizes the robustness of NMI metric while keeping the optimization characteristics of SSD-based Lucas-Kanade (LK) tracking methods. To validate the robustness and accuracy of the proposed approach, several experiments are performed on synthetic datasets as well as real image datasets. The experimental results demonstrate that our approach can provide fast, accurate pose estimation and obtain better tracking performance over standard SSD-based methods in most cases.
AB - This paper presents a novel visual tracking approach that combines the NMI metric and the traditional SSD metric within a gradient-based optimization frame, which can be used for direct visual odometry and SLAM. We firstly derivate the closed form expression for first- and second-order analytical NMI derivatives under the assumption of rigid-body transformations, which then can be used by subsequent Newton-like optimization methods. Then we develop a robust tracking scheme that utilizes the robustness of NMI metric while keeping the optimization characteristics of SSD-based Lucas-Kanade (LK) tracking methods. To validate the robustness and accuracy of the proposed approach, several experiments are performed on synthetic datasets as well as real image datasets. The experimental results demonstrate that our approach can provide fast, accurate pose estimation and obtain better tracking performance over standard SSD-based methods in most cases.
KW - Direct visual tracking
KW - Nonlinear optimization
KW - Normalized mutual information
KW - Sum of squared differences
UR - http://www.scopus.com/inward/record.url?scp=85059357461&partnerID=8YFLogxK
U2 - 10.1117/12.2500857
DO - 10.1117/12.2500857
M3 - Conference contribution
AN - SCOPUS:85059357461
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Optical Metrology and Inspection for Industrial Applications V
A2 - Yoshizawa, Toru
A2 - Zhang, Song
A2 - Han, Sen
A2 - Han, Sen
PB - SPIE
T2 - Optical Metrology and Inspection for Industrial Applications V 2018
Y2 - 11 October 2018 through 13 October 2018
ER -