sSfS: Segmented Shape from Silhouette Reconstruction of the Human Body.
Sensors (Basel)
; 22(3)2022 Jan 25.
Article
en En
| MEDLINE
| ID: mdl-35161670
ABSTRACT
Three-dimensional (3D) shape estimation of the human body has a growing number of applications in medicine, anthropometry, special effects, and many other fields. Therefore, the demand for the high-quality acquisition of a complete and accurate body model is increasing. In this paper, a short survey of current state-of-the-art solutions is provided. One of the most commonly used approaches is the Shape-from-Silhouette (SfS) method. It is capable of the reconstruction of dynamic and challenging-to-capture objects. This paper proposes a novel approach that extends the conventional voxel-based SfS method with silhouette segmentation-segmented Shape from Silhouette (sSfS). It allows the 3D reconstruction of body segments separately, which provides significantly better human body shape estimation results, especially in concave areas. For validation, a dataset representing the human body in 20 complex poses was created and assessed based on the quality metrics in reference to the ground-truth photogrammetric reconstruction. It appeared that the number of invalid reconstruction voxels for the sSfS method was 1.7 times lower than for the state-of-the-art SfS approach. The root-mean-square (RMS) error of the distance to the reference surface was also 1.22 times lower.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Cuerpo Humano
/
Imagenología Tridimensional
Límite:
Humans
Idioma:
En
Revista:
Sensors (Basel)
Año:
2022
Tipo del documento:
Article
País de afiliación:
Polonia