Sex Classification via 2D-Skeletonization

Miguel Contreras-Murillo, Sergio G. de-los-Cobos-Silva, Pedro Lara-Velázquez, Eric A. Rincón-García, Román A. Mora-Gutiérrez and Miguel Á. Gutiérrez-Andrade

Mathematical Problems in Engineering, 2020, vol. 2020, 1-12

Abstract:

Sex classification is a challenging open problem in computer vision. It is useful from statistics up to people recognition on surveillance video. So far, the best performance can be achieved by using 3D cameras, but this approach requires the use of some especial hardware. Other 2D approaches achieve good results on normal situations but fail when the person wears loose clothing and carries bags or the camera angle changes as they rely on calculating borders, silhouettes, or the energy of the person in the image. This work aims to provide a novel sex classification methodology based on the creation of a virtual skeleton for each individual from 2D images and video; then, the distances between some points of the skeleton are measured and work as input of a sex classifier. This improves the results since clothing, bags, and the camera angle affect little the skeletonization process.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2020/6182654.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2020/6182654.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6182654

DOI: 10.1155/2020/6182654

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().