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Human height estimation using visual geometry and feature learning
Author(s)
Date Issued
January 1, 2021
Type
Conference Paper
Abstract
Many existing video surveillance systems use human characteristics like face, height, and gait to identify a person. This paper proposes a human height estimation approach using visual geometry and feature learning that makes an estimate from a video clip of a person. An experiment was conducted to evaluate the performance of the approach. The approach achieved an average percentage final height estimate of 100.59 % (actual height = 100%), better than a previously reported estimate of 98.8% in the literature achieved by another approach. A successful further development of this approach would directly benefit forensic science investigators.
Citation
Proceedings IEEE International Symposium on Circuits and Systems, 2021-May, 2021