DocumentCode :
3089162
Title :
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
Link To Document :
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