Automatic Detection of 2D Human Postures Based on Single Images

Author

Souto, Humberto, Jr. ; Musse, Soraia Raupp

Author_Institution

Grad. Programme in Comput. Sci., Pontificia Univ. Catolica do Rio Grande do Sul - PUCRS, Porto Alegre, Brazil

fYear

2011

fDate

28-31 Aug. 2011

Firstpage

48

Lastpage

55

Abstract

Estimating human pose in static images is a challenging task due to the high dimensional state space, presence of image clutter and ambiguities of image observations. In this paper we propose a method to automatically detect human poses in a single image, based on a 2D model combined with anthropometric data. Furthermore, we use artificial neural networks to detect high level information about the human posture. Experimental results showed that the proposed technique performs well in non trivial images.

Keywords

clutter; neural nets; pose estimation; 2D human posture detection; 2D model; anthropometric data; artificial neural network; automatic detection; high dimensional state space; high level information detection; human pose estimation; image clutter; image observation; single image; static image; Face; Humans; Image segmentation; Joints; Legged locomotion; Skin; Training; artificial neural network; posture detection; single image;

fLanguage

English

Publisher

ieee

Conference_Titel

Graphics, Patterns and Images (Sibgrapi), 2011 24th SIBGRAPI Conference on

Conference_Location

Maceio, Alagoas

Print_ISBN

978-1-4577-1674-4

Type

conf

DOI

10.1109/SIBGRAPI.2011.4

Filename

6134734