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. US2024193899A1.
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. US2024193899A1).
@misc{c39fb255906b4f688efde600d5693050,
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 = "US2024193899A1",
}