Name
Abstract | ||
|---|---|---|
In this paper, we propose a novel real-time method for tracking planar edge templates. This method tracks an edge template by estimating its homography transformations with respect to the sampled edge pixels detected from the incoming frames. Particularly, we define a cost function based on a new feature map of the to-be-tracked edge template and optimize it by a Lucas-Kanade-like algorithm. The feature map is defined as the fourth root of the distance transform. Our method operates on just edges so that it is good at tracking those low textured targets, such as hollow targets (mug rim), thin targets (cable, ring) and non-Lambertian objects (disc). We validate and compare our method with four other methods on five newly collected real-world video sequences. The results achieves the lowest overall average error (1.58 pixels) and also outperforms others in terms of success rate. The per frame processing time of about 30 ms proves that our method is acceptable in realtime applications. The code and dataset are publicly available at: http://webdocs.cs.ualberta.ca/~xuebin/. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IROS.2018.8593551 | 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
Keywords | Field | DocType |
homography estimation,planar edge templates,homography transformations,sampled edge pixels,Lucas-Kanade-like algorithm,low textured targets,edge template tracking,nonLambertian objects,video sequences | Computer vision,Computer science,Homography,Distance transform,Planar,Artificial intelligence,Pixel,Template,Template tracking,nth root | Conference |
ISSN | ISBN | Citations |
2153-0858 | 978-1-5386-8095-7 | 0 |
PageRank | References | Authors |
0.34 | 11 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuebin Qin | 1 | 19 | 2.23 |
| Shida He | 2 | 2 | 2.73 |
| Zichen Zhang | 3 | 1 | 2.72 |
| Masood Dehghan | 4 | 49 | 7.11 |
| Jun Jin | 5 | 0 | 0.34 |
| Martin Jagersand | 6 | 100 | 10.96 |