Methods are disclosed for generating a training dataset of concealed shapes and corresponding unveiled shapes of a body for training a neural network. These methods may include generating with the aid of computing means a first dataset comprising a plurality of first surface representations representative of a plurality of bare shapes of a plurality of bodies. The plurality of bare shapes are concealed virtually by means of a computer implemented program in order to obtain a plurality of simulated concealed shapes of the plurality of bodies. The plurality of simulated concealed shapes are applied to a scanning simulator, the scanning simulator generating a second dataset comprising a plurality of second surface representations representative of the plurality of simulated concealed shapes.
Hu, P, Munteanu, A, Nourbakhsh Kaashki, N & Sturges, S, Methods of estimating a bare body shape from a concealed scan of the body, Patent No. US11922593B.
Hu, P., Munteanu, A., Nourbakhsh Kaashki, N., & Sturges, S. (2024). Methods of estimating a bare body shape from a concealed scan of the body. (Patent No. US11922593B).
@misc{d79a414933c844e28bdb8c909f46ac81,
title = "Methods of estimating a bare body shape from a concealed scan of the body",
abstract = "Methods are disclosed for generating a training dataset of concealed shapes and corresponding unveiled shapes of a body for training a neural network. These methods may include generating with the aid of computing means a first dataset comprising a plurality of first surface representations representative of a plurality of bare shapes of a plurality of bodies. The plurality of bare shapes are concealed virtually by means of a computer implemented program in order to obtain a plurality of simulated concealed shapes of the plurality of bodies. The plurality of simulated concealed shapes are applied to a scanning simulator, the scanning simulator generating a second dataset comprising a plurality of second surface representations representative of the plurality of simulated concealed shapes. ",
author = "Pengpeng Hu and Adrian Munteanu and \{Nourbakhsh Kaashki\}, Nastaran and Stephan Sturges",
year = "2024",
language = "English",
type = "Patent",
note = "US11922593B",
}