Toward Low Latency Gesture Control Using Smart Camera Network
Abstract
Real-world gesture controlled applications are not yet widely present mainly due to strong practical constraints. As a step toward realizing a practical, affordable, low-power, real time, low-latency gesture control, we present a smart camera system and an algorithm for upper body pose reconstruction implemented on the system. A single-instruction multiple-data (SIMD) processor on a smart camera platform is used to detect person head and hands. The detected hand and head candidate positions are then transmitted to a central processor (a PC) where the data is combined and final decisions are made. Implementation of a computer vision algorithm on the SIMD camera processor is presented. We also describe the whole wireless smart camera system and analyze the performance and practical issues.
Cite
Text
Zivkovic et al. "Toward Low Latency Gesture Control Using Smart Camera Network." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563150Markdown
[Zivkovic et al. "Toward Low Latency Gesture Control Using Smart Camera Network." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/zivkovic2008cvprw-low/) doi:10.1109/CVPRW.2008.4563150BibTeX
@inproceedings{zivkovic2008cvprw-low,
title = {{Toward Low Latency Gesture Control Using Smart Camera Network}},
author = {Zivkovic, Zoran and Kliger, Vitaly and Kleihorst, Richard P. and Danilin, Alexander and Schueler, Ben and Arturi, Giuseppe and Chang, Chung-Ching and Aghajan, Hamid K.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2008},
pages = {1-8},
doi = {10.1109/CVPRW.2008.4563150},
url = {https://mlanthology.org/cvprw/2008/zivkovic2008cvprw-low/}
}