期刊文献+

限于人体肢体运动的轻量型生物信息红外获取方法的研究(英文)

Limb-specific Infrared Sensing towards Lightweight Biometrics
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摘要 本文提出了一种限于人体肢体运动特征红外感知的方法并用实验下该方法在轻量级人体生物信息获取中的应用效果。本文的传感方法采用了热释电红外传感阵列来获取由人体运动产生的生物信息。人体运动生物特征信息由一个双层结构获取过程组成:在底层由物理层的热释电红外传感阵列组成的限于肢体运动的感和层,本层具体关注多角度多肢体局部的细粒度运动特征感知;上层的运动特征感知组成全局的逻辑识别综合分析,本层通过综合同步身体体域级的运动信息合成生物特征,本文提出的传感方法在多人约束路径步态识别了进行实验,并采用矢量识别技术进行了验证获得了较好的识别效果。 This paper presents a limb-specific infrared sensing paradigm and its application in building a lightweightbiometric system. The proposed sensing paradigm explores the novel use of pyroelectric infrared (PIR) sensor arrays inpursuit of unifying biometric feature acquisition and motion capturing into an infrared sensing framework. A two-layerstructure is used to organize the biometric feature acquisition process: the limb-specific sensing is physically implementedwith PIR sensor arrays at the bottom layer, which focuses on capturing the limb-level biometrics associated with walker'slimb-level movements from multi-view; the global locomotion is logically characterized at the top layer, which synergies thebody-level biometrics to exhibit the coordination habits of walker's limb-level movements. The application of the proposedsensing paradigm to lightweight human identification is addressed in the context of the path-constrained walker recognitionwith the vector quantization technique. Experimental studies are conducted to validate the proposed method.
出处 《惠州学院学报》 2016年第3期46-54,共9页 Journal of Huizhou University
基金 国家自然科学基金项目(61407774) 惠州市科技计划项目(2015B010002010)
关键词 生物信息 限于特征感知 热释电红外传感阵列 Biometrics, Feature-specific Sensing, Pyroelec-tric Infrared Sensor Arrays
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参考文献28

  • 1A. K. Jain, A. Ross, and S. Prabhakar, "An introduction to biometric recognition," IEEE Trans. on Circuits and Systems for Video Technology, vol. 14, pp. 4-20, 2004.
  • 2J. G, "Visual perception of biologicai motion and a model for its analysis," Perception Psychophysics, vol. 14, pp. 201-211, 1973.
  • 3M. M. P., "Gait as a total pattern of movement," American Journal of PhysicalMedicine, vol. 46, pp. 290-332, 1967.
  • 4D. Gafurov and E. Snekkenes, "Gait recognition using wearable motion recording sensors," EURASIP J. Adv. Signal Process, vol. 2009, pp. 1- 16, 2009.
  • 5S. Sarkar, P. J. Phillips, Z. Liu, I. R. Vega, P. Grother, and K. W. Bowyer, "The humanid gait challenge problem: Data sets, performance, and analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, pp. 162-177, 2005.
  • 6J. Han and B. Bhanu, "Human activity recognition in thermal infrared imagery," in CVPR '05: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops, 2005, p. 17.
  • 7D. Ming, Z. Xue, L. Meng, B. Wan, Y. Hu, and K. Luk, "Identification of humans using infrared gait recognition," in VECIMS'09: Proceedings of the 2009 IEEE international conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2009.
  • 8S. L. Daehee Kim and J. Paik, "Active shape model-based gait recogni- tion using infrared images," International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 2, no. 4, December 2009.
  • 9J. L. M. L. Tong Liu, Yaqi Chu and G. Wang, "Distributed infrared bit- metric sensing for lightweight human identification systems," in WC1CA 2010:8th World Congress on Intelligent Control and Automation., to be appear in.
  • 10M. A. Neifeld and P. Shankar, "Feature-specific imaging" Appl. Opt., vol. 42, no. 17, pp. 3379-3389, 2003.

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