Abstract
Traditional plane alignment techniques are typically performed between pairs of frames. In this paper we present a method for extending existing two-frame planar-motion estimation techniques into a simultaneous multi-frame estimation, by exploiting multi-frame geometric constraints of planar surfaces. The paper has three main contributions: (i) we show that when the camera calibration does not change, the collection of all parametric image motions of a planar surface in the scene across multiple frames is embedded in a low dimensional linear subspace; (ii) we show that the relative image motion of multiple planar surfaces across multiple frames is embedded in a yet lower dimensional linear subspace, even with varying camera calibration; and (iii) we show how these multi-frame constraints can be incorporated into simultaneous multi-frame estimation of planar motion, without explicitly recovering any 3D information, or camera calibration. The resulting multi-frame estimation process is more constrained than the individual two-frame estimations, leading to more accurate alignment, even when applied to small image regions.
Original language | English |
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Pages (from-to) | 151-156 |
Number of pages | 6 |
Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
Volume | 1 |
State | Published - 1999 |
Externally published | Yes |
Event | Proceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99) - Fort Collins, CO, USA Duration: 23 Jun 1999 → 25 Jun 1999 |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition