High-speed Motion Analysis with Multi-exposure Images
We propose a method to estimate dense motion vector fields from multi-exposure images. Our approach relies on finding a sparse set of correspondences between features in a single-exposure image and each exposure in a multi-exposure image using a global optimization technique. We iteratively establish such matches, compute a set of locally restricted transformations for the matches, and construct a dense motion vector field in a multiresolution framework. The estimation of the number of necessary transformations and the regions of influence is guided by superpixel segmentation of the image. We present results for multi-exposure photos of different dynamic scenes.
| Author(s): | Christian Linz, Timo Stich, Marcus Magnor |
|---|---|
| Published: | October 2008 |
| Type: | Article in conference proceedings |
| Book: | Proc. Vision, Modeling and Visualization (VMV) |
| Presented at: | Vision, Modeling and Visualization (VMV) 2008 |
@inproceedings{linz2008motionanalysis,
title = {High-speed Motion Analysis with Multi-exposure Images},
author = {Linz, Christian and Stich, Timo and Magnor, Marcus},
booktitle = {Proc. Vision, Modeling and Visualization ({VMV})},
organization = {Eurographics},
month = {Oct},
year = {2008}
}
Authors
-
Christian Linz
Fmr. Researcher -
Timo Stich
Fmr. Researcher -
Marcus Magnor
Director, Chair