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An overview of spatial-temporal human gesture recognition under degraded environments using integral imaging
Author(s): Xin Shen; Hee-Seung Kim; Satoru Komatsu; Adam Markman; Bahram Javidi
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Paper Abstract

We overview a previously reported method for spatial-temporal human gesture recognition under degraded environmental conditions using three-dimensional (3D) integral imaging (InIm) technology with correlation filters. The degraded conditions include low illumination environment and occlusion in front of the human gesture. The human gesture is captured by passive integral imaging, the signal is then processed using computational reconstruction algorithms and denoising algorithms to decrease the noise and remove partial occlusion. Gesture recognition is finally processed using correlation filters. Experimental results show that the proposed approach is promising for human gesture recognition under degraded environmental conditions compared with conventional recognition algorithms.

Paper Details

Date Published: 22 May 2019
PDF: 7 pages
Proc. SPIE 10997, Three-Dimensional Imaging, Visualization, and Display 2019, 109970X (22 May 2019); doi: 10.1117/12.2521338
Show Author Affiliations
Xin Shen, Univ. of Connecticut (United States)
Hee-Seung Kim, Univ. of Connecticut (United States)
Satoru Komatsu, Univ. of Connecticut (United States)
Adam Markman, Univ. of Connecticut (United States)
Bahram Javidi, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 10997:
Three-Dimensional Imaging, Visualization, and Display 2019
Bahram Javidi; Jung-Young Son; Osamu Matoba, Editor(s)

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