提出了一种基于图像的唤醒行为检测系统,并对捕获图像中亮度的波动进行了自适应

H. Satoh, Takayuki Ohkura, F. Takeda
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引用次数: 4

摘要

最近,老年人在护理设施或医院从床上摔下的事故有所增加。为了防止这些事故的发生,我们开发了基于神经网络的唤醒行为检测系统。在本文中,现有系统利用临床现场采集的图像进行检测的成功率不足是一个问题。因此,我们在临床现场分析捕获的图像。从直方图分析的结果可以看出,亮度量的波动会降低检测能力。因此,为了减少亮度量的影响,需要对捕获图像的直方图进行均衡化处理。最后,用数值方法证明了直方图均衡化可以减小亮度的波动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proposal for the awakening behavior detection system using images and adaptation for fluctuation of brightness quantity in the captured image
Recently, accidents such that seniors fall down from the bed in care facilities or hospitals are increased. To prevent these accidents, we have developed the awakening behavior detection system using Neural Network. In this paper, it is a problem that the detection success rate of the current system using captured image in the clinical site is not enough. So, we analyze the captured image in the clinical site. From the result of the histogram analysis, it proves that the fluctuation of brightness quantity makes decrease the detection capability. Therefore, to decrease the influence of the brightness quantity, the histogram of the captured image should be equalized. Finally, we show that the histogram equalization reduces fluctuation of brightness quantity numerically.
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