Human Height Estimation Using Visual Geometry and Feature Learning

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 =3D 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.