Tracking People Across Multiple Non-Overlapping RGB-D Sensors
Abstract
This work presents the development of a surveillance system for monitoring wide area indoor spaces using multiple Kinect devices. The data from these sensors, configured with the widest possible coverage, is integrated into a single coordinate system using a novel calibration technique for non-overlapping range sensors. Moving 3D pixels from each Kinect are transformed into a "plan view" map of activity where the detection and tracking of people is executed. The detection of people is a two step process, data binning and non maxima suppression. The tracking of people is based on the mean-shift algorithm optimized with the prediction step of the Kalman Filter.
Cite
Text
Almazan and Jones. "Tracking People Across Multiple Non-Overlapping RGB-D Sensors." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2013. doi:10.1109/CVPRW.2013.124Markdown
[Almazan and Jones. "Tracking People Across Multiple Non-Overlapping RGB-D Sensors." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2013.](https://mlanthology.org/cvprw/2013/almazan2013cvprw-tracking/) doi:10.1109/CVPRW.2013.124BibTeX
@inproceedings{almazan2013cvprw-tracking,
title = {{Tracking People Across Multiple Non-Overlapping RGB-D Sensors}},
author = {Almazan, Emilio J. and Jones, Graeme A.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2013},
pages = {831-837},
doi = {10.1109/CVPRW.2013.124},
url = {https://mlanthology.org/cvprw/2013/almazan2013cvprw-tracking/}
}