Occupancy Estimation from Thermal Images
Computer Vision and Pattern Recognition
2021-10-18 v1 Artificial Intelligence
Abstract
We propose a non-intrusive, and privacy-preserving occupancy estimation system for smart environments. The proposed scheme uses thermal images to detect the number of people in a given area. The occupancy estimation model is designed using the concepts of intensity-based and motion-based human segmentation. The notion of difference catcher, connected component labeling, noise filter, and memory propagation are utilized to estimate the occupancy number. We use a real dataset to demonstrate the effectiveness of the proposed system.
Cite
@article{arxiv.2110.07796,
title = {Occupancy Estimation from Thermal Images},
author = {Zishan Qin and Dipankar Chaki and Abdallah Lakhdari and Amani Abusafia and Athman Bouguettaya},
journal= {arXiv preprint arXiv:2110.07796},
year = {2021}
}
Comments
4 pages, 2 figures. This is an accepted demo paper and to be published in the proceedings of 19th International Conference on Service Oriented Computing (ICSOC 2021)