Shape-Time Photography
Abstract
We introduce a new method to describe shape relationships over time in a photograph. We acquire both range and image information in a sequence of frames using a stationary stereo camera. From the pictures taken, we compute a composite image consisting of the pixels from the surfaces closest to the camera over all the time frames. Through occlusion cues, this composite reveals 3-D relationships between the shapes at different times. We call the composite a shape-time photograph. Small errors in stereo depth measurements can create artifacts in the shape-time images. We correct most of these using a Markov network to estimate the most probable front-surface pixel, taking into account (a) the stereo depth measurements and their uncertainties, and (b) spatial continuity assumptions for the time-frame assignments of the front-surface pixels.
Cite
Text
Freeman and Zhang. "Shape-Time Photography." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2003. doi:10.1109/CVPR.2003.1211465Markdown
[Freeman and Zhang. "Shape-Time Photography." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2003.](https://mlanthology.org/cvpr/2003/freeman2003cvpr-shape/) doi:10.1109/CVPR.2003.1211465BibTeX
@inproceedings{freeman2003cvpr-shape,
title = {{Shape-Time Photography}},
author = {Freeman, William T. and Zhang, Hao},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2003},
pages = {151-157},
doi = {10.1109/CVPR.2003.1211465},
url = {https://mlanthology.org/cvpr/2003/freeman2003cvpr-shape/}
}