Result: Visual reconstruction of ground plane obstacles in a sparse view robot environment

Title:
Visual reconstruction of ground plane obstacles in a sparse view robot environment
Authors:
LAGANIERE, R, HAJJDIAB, H, MITICHE, A
Source:
Special Issue on SPM 2005Graphical models. 68(3):282-293
Publisher Information:
San Diego, CA: Elsevier, 2006.
Publication Year:
2006
Physical Description:
print, 38 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Automatique théorique. Systèmes, Control theory. Systems, Robotique, Robotics, Conformisme, Conformity, Conformismo, Courbe niveau, Contour line, Curva nivel, Equation Euler, Euler equation, Ecuación Euler, Equation Lagrange, Lagrange equation, Ecuación Lagrange, Equation évolution, Evolution equation, Ecuación evolución, Erreur systématique, Bias, Error sistemático, Image tridimensionnelle, Tridimensional image, Imagen tridimensional, Infographie, Computer graphics, Gráfico computadora, Information visuelle, Visual information, Información visual, Mesure information, Information measure, Medida información, Modélisation, Modeling, Modelización, Orienté objet, Object oriented, Orientado objeto, Reconstruction image, Image reconstruction, Reconstrucción imagen, Robotique, Robotics, Robótica, Segmentation image, Image segmentation, Stabilité numérique, Numerical stability, Estabilidad numérica, Surface lisse, Smooth surface, Superficie lisa, Surface plane, Plane surface, Superficie plana, Texturation, Texturación, Topologie, Topology, Topología, Traitement image, Image processing, Procesamiento imagen, Vision ordinateur, Computer vision, Visión ordenador, 3D reconstruction, Ground plane obstacle, Level sets, Photo-consistency, Shape-from-silhouette, Widely separated view matching
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
VIVA Research Laboratory, School of Information Technology and Engineering, University of Ottawa, Ottawa, Ont., KIN 6N5, Canada
Institut National de la Recherche Scientifique, INRS-EMT, Montreal, Que., H5A 1K6, Canada
ISSN:
1524-0703
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=17869636
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17869636
Database:
PASCAL Archive

Further Information

The purpose of this study is to investigate a geometric/level set method to locate ground plane objects in a robot environment and reconstruct their structure from a collection of sparse views. In a first step, a model of the ground plane surface, on which the robot is operating, is obtained through the matching of the available views. This wide-baseline matching of the ground plane views allows also to compute camera pose information associated with each of these views. Based on the information obtained, reconstruction of the obstacles proceeds by minimizing an energy functional containing three terms: a term of shape-from-silhouettes consistency to characterize the ground plane objects structure and to account for possibly non-textured object surfaces; a term of visual information consistency to measure the conformity of the objects surface visual information to the acquired images; and finally, a term of regularization to bias the solution toward smooth object surfaces. The functional is minimized following the associated Euler-Lagrange surface evolution descent equations, implemented via level set PDEs to allow changes in topology while ensuring numerical stability. We provide examples of verification of the scheme on real data.