从模糊视频中估计占用率:一个多方面的方法,考虑隐私
Md Sakib Galib Sourav1, Ehsan Yavari1, Xiaomeng Gao1
1Department of Electrical & Computer Engineering, University of Hawai'i at Manoa, Honolulu, HI 96822, USA.
Sensors (Basel, Switzerland)
|June 27, 2024
概括
本研究介绍了使用模糊视频进行建筑占用率估计的隐私保护方法. 一种联合的消除模糊和密度估计技术实现了16.29%的计数误差,平衡了准确性和乘客隐私.
科学领域:
- 计算机视觉 计算机视觉
- 建筑的能源效率 建筑的能源效率
- 人与计算机的交互
背景情况:
- 准确的建筑占用数据对于资源分配和应急响应至关重要.
- 传统的HVAC系统假定占用率最高,导致大量的能源浪费 (超过50%的美国建筑能源预算).
- 基于摄像头的占用率估计提供了高精度,但引发了隐私问题.
研究的目的:
- 开发和评估使用故意模糊的视频来保护隐私的占用率估计方法.
- 研究基于运动和运动独立的技术来计算占用率.
- 分析估计准确性和乘客视觉隐私之间的权衡.
主要方法:
- 提出了一种保护隐私的基于运动的占用计数技术.
- 开发了运动独立的方法,包括基于检测和基于密度估计的方法.
- 利用代统计和基于深度学习的模糊清除来提高运动独立方法的准确性.
- 在原始,模糊和消除模糊的上使用图像质量评估指标评估隐私影响.
主要成果:
- 代统计模糊清除和密度估计的组合实现了16.29%的计数误差.
- 这种方法在准确性方面超过了其他拟议的方法.
- 该研究提供了关于占用率估计准确性和视觉隐私保护之间的平衡的见解.
结论:
- 提出了一种新的方法,平衡占用率估计的准确性和乘客隐私.
- 与密度估计的代统计模糊化显示出对隐私意识占用计数的承诺.
- 需要进一步的研究,以充分优化保护隐私的占用率估计系统.
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