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移动机器人平台下基于视觉的摔倒检测方法 被引量:1

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摘要 当前智能机器人已开始进入家庭服务行业。随着人口的老龄化,如何利用家庭服务机器人来看护老人,尤其是判断老年人是否摔倒,是一个具有很好理论和应用价值的研究课题。本文在移动机器人平台下,提出了一种基于单张静态图片的平躺人体检测方法。该方法首先利用积分通道特征来刻画人体的轮廓特征;然后采用Ada Boost训练一个分类器来判断当前图像中的某个检测窗口是否包含平躺人体;最后采用滑动窗口法在图像的尺度和旋转空间内进行扫描,并进行非极大值抑制,从而确定平躺人体的位置。在我们自己构建的室内平躺人体数据集上,验证了该方法的有效性。
作者 刘德建
出处 《电子技术与软件工程》 2015年第18期76-79,共4页 ELECTRONIC TECHNOLOGY & SOFTWARE ENGINEERING
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  • 1C.-S. Lin, H.C. Hsu,~.-L. Lay, C.-C. Chiu, and C.-S. Chao, Wearable device for real-time monitoring of human falls [J]. Measurement, vol. 40, nos. 9-10, pp. 831-840, 2007.
  • 2F. Bianchi, S. Redmond, M. Narayanan, S. Cerutti,and N. Lovell,Barometric pressure and trlaxial accelerometry- based falls event detection [J]. IEEE Trans. Neural System and Rehabilitation Engineering, vol. 18, no. 6, pp. 619-627,2010.
  • 3K. Ozcan, h.K. Mahabalagiri,M. Casares, and S.~elipasalar, Automatic fall detection and activity classification by a wearable embedded smart camera[J]. IEEE J. gmerging and Selected Topics in Circuits and Syst ems, vol. 3, no. 2, pp. 125-136,2013.
  • 4A. Arcelus, I. Veledar, R. 6oubran, F. Knoefel,H. Sveistrup, and M. Bilodeau, Measurements of sit-to- stand timing and symmetry from bed pressure sensors[J].IEEE Trans. Instrumentation and Measurement, vol. 60, no. 5, pp. 1732-1740,2011.
  • 5Y. Zigel,D. Litvak, and I. Gannot, A method for automatic fall detection of elderly people using ftoor vibrations and sound- Proof of concept on human mimicking doll falls[J]. IEEE Trans. Biomedical Engineering, vol. 56, no. 12, pp. 2858-2867,2009.
  • 6H. Rimminen,/.Lindstrom, M. Linnavuo, and R. Sepponen, Detection of fails among the elderly by a floor sensor using the electric near field[J]. IEEE Trans. Information Technology in Biomedicine, vol. 14, no. 6, pp. 1475- 1476,2010.
  • 7S.-H. Huang and Y.-C. Pan, "Learning- based fall detection using RGB-D cameras [A].in Proc. IEEE Int. Conf. Machine Vision Applications[C]. pp. 439-442,2013.
  • 8M. Shoaib, R. Dragon, and J. Ostermann, View-invariant fall detection for elderly in real home environment[A].in Proc. Pacific-Rim Symp. Image Video Technology [C], 2010.
  • 9Z.Z. Htike, S. Egerton, and Y.C. Kuang, A monocular view-invariant fall detection system for the elderly in assisted home environments[A], in Proc. Int. Conf, Intelligent Environment [C]2011.
  • 10B. Mirmahboub, S. Samavi, N. Karimi, and S. Shirani, Automatic monocular system for human fall detection based on variations in silhouette area [J]. IEEE Trans. Biomedical Engineering, vol. 60, no. 2, pp. 427-436,2013.

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