兴趣区大小对视频放大心率评估的影响

L. Kassab, Andrew J. Law, Bruce Wallace, J. Larivière-Chartier, R. Goubran, F. Knoefel
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引用次数: 7

摘要

快速筛查人们的传染病症状的能力对于减少疾病在长期护理机构和拥挤的公共场所的传播非常重要。为了实现这一目标,一种选择可能是测量生命体征的非接触式传感器阵列。在这项工作中,我们介绍了通过应用于可见光红/绿/蓝(RGB)视频记录的视频放大技术来评估心率的初步结果。这项工作特别探讨了感兴趣区域大小对心率测量准确性的影响。人们脸上可见的皮肤可能会被头发或口罩遮挡,因此需要能够补偿这些影响的算法和方法。结果表明,许多小区域的组合可以替代单一的大区域。小区域的最佳性能是平均绝对误差为9.9%,而较大区域的最佳误差性能<3%。研究还表明,对于覆盖大部分/全部面部的较大区域,身体运动比使用遮挡部分面部的面罩更能降低性能。这项工作为进一步开发可靠的非接触式健康筛查解决方案奠定了基础。
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Effects of Region of Interest Size on Heart Rate Assessment through Video Magnification
The ability to quickly screen people for symptoms of infectious disease is important to reduce disease transmission in long term care facilities and crowded public spaces. To achieve this goal, one option could be non-contact sensor arrays that measure vital signs. In this work, we present initial results for the assessment of heart rate through video magnification techniques applied to visible light Red/Green/Blue (RGB) video recordings of the face. The work specifically explores the effect of region of interest size on the accuracy of heart rate measurements. The visible skin on a person’s face can be obscured by hair or face masks, leading to a need for algorithms and methods that can compensate for these effects. The results show the potential for the combination of many small regions as an alternative to a single large region. The best performance for small regions is a mean absolute error of 9.9% while larger regions performed better with the best error performance of <3%. The work also shows that for larger regions covering most/all of the face, body motion reduces the performance more than the use of a face mask that obscures a portion of the face. This work provides the foundation for further development of robust non-contact health screening solutions.
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