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Volume 44 Issue 3
Mar.  2022
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ZHANG Yutong, ZHAI Xuping, NIE Hong. Deep Learning Method for Action Recognition Based on Low Resolution Infrared Sensors[J]. Infrared Technology , 2022, 44(3): 286-293.
Citation: ZHANG Yutong, ZHAI Xuping, NIE Hong. Deep Learning Method for Action Recognition Based on Low Resolution Infrared Sensors[J]. Infrared Technology , 2022, 44(3): 286-293.
shu

Deep Learning Method for Action Recognition Based on Low Resolution Infrared Sensors

  • 1.

    Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200444, China

  • 2.

    Department of Technology, University of Northern Iowa, Cedar Falls 50614-0507, USA

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  • Received Date: April 20, 2021
  • Revised Date: June 01, 2021
    Graphical Abstract
    • Abstract
  • In recent years, action recognition has become a popular research topic in the field of computer vision. In contrast to research on video or images, this study proposes a two-stream convolution neural network method based on temperature data collected by a low-resolution infrared sensor. The spatial and temporal data were input into the two-stream convolution neural network in the form of collected temperature data, and the class scores of the spatial and temporal stream networks were late weighted and merged to obtain the final action category. The results indicate that the average accuracy of recognition can reach 98.2% on the manually collected dataset and 99% for bending, falling, and walking actions, indicating that the proposed net can recognize actions effectively.
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    • References (19)
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