Using Computer Vision for 3D Probabilistic Reconstruction and Motion Tracking

Author

Simas, Gisele M. ; Fickel, Guilherme P. ; Novelo, Lucas ; Botelho, Silvia S C ; de Bem, R.A.

Author_Institution

Centre de Cienc. Computacionais - C3, Univ. Fed. do Rio Grande - FURG, Rio Grande, Brazil

fYear

2009

fDate

23-25 Nov. 2009

Firstpage

119

Lastpage

124

Abstract

This paper presents an approach to the 3D visual tracking problem into multi-camera environments. This proposal executes the markerless visual tracking observing the environment through a model based in a volumetric reconstruction technique, called 3D Probabilistic Occupancy Grids, which is still seldom used for this purpose. The target is tracked by the use of Expectation-Maximization algorithm with an object representation model constructed with Gaussians blobs representing the object body parts.

Keywords

Gaussian processes; cameras; computer vision; expectation-maximisation algorithm; image reconstruction; motion estimation; tracking; 3D probabilistic occupancy grid; 3D probabilistic reconstruction; 3D visual tracking problem; Gaussians blob; computer vision; expectation maximization algorithm; markerless visual tracking; motion tracking; multicamera environment; object body part; object representation model; volumetric reconstruction technique; Delta modulation; Pixel; Probabilistic logic; Solid modeling; Target tracking; Three dimensional displays; Visualization; rastreamento visual; reconstrução probabilística 3D; visão computacional;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Modeling (MCSUL), 2009 Third Southern Conference on

Conference_Location

Rio Grande

Print_ISBN

978-1-4244-5980-3

Type

conf

DOI

10.1109/MCSUL.2009.18

Filename

5597975