Integrating Moving Edge Information Along a 2D Trajectory in Densely Sampled Imagery
Abstract
The author seeks to exploit the inherent continuity of visual motion by examining the trajectory of a moving edge in densely sampled imagery. Past edge motion is propagated ahead of the moving edge along the trajectory; this information is then used to evaluate current motion measurements and compute important feature properties. Two related temporal image features are presented. Temporal persistence is the period of time over which a spatial feature has stably persisted in the image plane. Consistent edge motion occurs when an edge moves in a manner which is consistent with its previous trajectory. These temporal features are important to object recognition because spatial structures which persist in a stable manner over time are likely to be structurally related to objects. Results on natural imagery are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Kahn. "Integrating Moving Edge Information Along a 2D Trajectory in Densely Sampled Imagery." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1988. doi:10.1109/CVPR.1988.196311Markdown
[Kahn. "Integrating Moving Edge Information Along a 2D Trajectory in Densely Sampled Imagery." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1988.](https://mlanthology.org/cvpr/1988/kahn1988cvpr-integrating/) doi:10.1109/CVPR.1988.196311BibTeX
@inproceedings{kahn1988cvpr-integrating,
title = {{Integrating Moving Edge Information Along a 2D Trajectory in Densely Sampled Imagery}},
author = {Kahn, Philip},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1988},
pages = {702-709},
doi = {10.1109/CVPR.1988.196311},
url = {https://mlanthology.org/cvpr/1988/kahn1988cvpr-integrating/}
}