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.
翻译:我们建议为智能环境建立一个非侵入性和隐私保护占用估计系统。 拟议的计划使用热图像来检测特定地区的人数。 占用估计模型使用基于强度和运动的人类分割概念来设计。 使用差异捕捉器、 连接部件标签、 噪音过滤和记忆传播的概念来估计占用数字。 我们使用一个真实的数据集来显示拟议系统的有效性 。