Keyframe-Based Real-Time Camera Tracking
Abstract
We present a novel keyframe selection and recognition method for robust markerless real-time camera tracking. Our system contains an offline module to select features from a group of reference images and an online module to match them to the input live video in order to quickly estimate the camera pose. The main contribution lies in constructing an optimal set of keyframes from the input reference images, which are required to approximately cover the entire space and at the same time minimize the content redundancy amongst the selected frames. This strategy not only greatly saves the computation, but also helps significantly reduce the number of repeated features so as to improve the camera tracking quality. Our system also employs a parallel-computing scheme with multi-CPU hardware architecture. Experimental results show that our method dramatically enhances the computation efficiency and eliminates the jittering artifacts.
Cite
Text
Dong et al. "Keyframe-Based Real-Time Camera Tracking." IEEE/CVF International Conference on Computer Vision, 2009. doi:10.1109/ICCV.2009.5459273Markdown
[Dong et al. "Keyframe-Based Real-Time Camera Tracking." IEEE/CVF International Conference on Computer Vision, 2009.](https://mlanthology.org/iccv/2009/dong2009iccv-keyframe/) doi:10.1109/ICCV.2009.5459273BibTeX
@inproceedings{dong2009iccv-keyframe,
title = {{Keyframe-Based Real-Time Camera Tracking}},
author = {Dong, Zilong and Zhang, Guofeng and Jia, Jiaya and Bao, Hujun},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2009},
pages = {1538-1545},
doi = {10.1109/ICCV.2009.5459273},
url = {https://mlanthology.org/iccv/2009/dong2009iccv-keyframe/}
}