Reducing depth ambiguity in 3D human pose and body shape estimation

Gakuto Maruyama; Naoshi Kaneko; Seiya Ito; Kazuhiko Sumi

doi:10.1117/12.2591151

16 July 2021 Reducing depth ambiguity in 3D human pose and body shape estimation

Gakuto Maruyama, Naoshi Kaneko, Seiya Ito, Kazuhiko Sumi

Proceedings Volume 11794, Fifteenth International Conference on Quality Control by Artificial Vision; 117940W (2021) https://doi.org/10.1117/12.2591151
Event: Fifteenth International Conference on Quality Control by Artificial Vision, 2021, Tokushima, Japan

Abstract

The previous 3D pose and shape estimation methods often suffer from the problem of depth ambiguity. Hence, we present a novel method to reduce the depth ambiguity by explicitly considering the depth of a person’s body surface. The key idea is minimizing the difference between the depth estimated from an input image and the projected depth of a reconstructed 3D mesh. This allows the proposed method to estimate 3D pose and body shape with plausible 3D joint locations. Evaluations show that the proposed method produces more appropriate 3D meshes and reduces both 3D pose and shape estimation errors.

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Gakuto Maruyama, Naoshi Kaneko, Seiya Ito, and Kazuhiko Sumi "Reducing depth ambiguity in 3D human pose and body shape estimation", Proc. SPIE 11794, Fifteenth International Conference on Quality Control by Artificial Vision, 117940W (16 July 2021); https://doi.org/10.1117/12.2591151

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KEYWORDS

3D modeling

3D image processing

RGB color model

3D image reconstruction

Shape analysis

Error analysis

Image restoration

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