Name
Abstract | ||
|---|---|---|
While a spherical image has a full field of view with a low resolution with respect to observed scenes, a perspective image has a narrow field of view with a high resolution with respect to observed scenes. Therefore, a spherical image and a perspective image are complementary to each other for the field of view and resolution; a visual system consisting of a spherical image and a perspective image can not only observe the entire surrounding environment, but also focus on a specific object with high resolution. In this paper we investigate the computation of the homography between a spherical image and a perspective image. First, the conventional homography of perspective images is reformulated to the case associating a spherical image to a perspective image. Next, we explain how to carry out feature matching between a full-view image and a perspective image for the computation of the homography. Finally, the experimental results of two applications are given to show the effectiveness of our proposed method. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/COASE.2018.8560371 | 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) |
Keywords | Field | DocType |
perspective image,full-view image,spherical image,feature matching,field-of-view,homography computation | Field of view,Spherical image,Computer vision,Computer science,Feature matching,Homography,Artificial intelligence,Computation | Conference |
ISSN | ISBN | Citations |
2161-8070 | 978-1-5386-3594-0 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shigang Li | 1 | 3 | 6.12 |
| Xiao-Wei Wang | 2 | 596 | 59.78 |
| Takahiro Kosaki | 3 | 1 | 1.76 |