This paper describes a scalable dense 3D recon- struction and navigation system suitable for real-time operation. The system represents the environment as the back-projection of a Delaunay triangulation of the omnidirectional image, estimated at each instant from two adjacent views. The cost being minimized (i.e., the reprojection error) is photometric rather than geometric, as in the majority of feature-based reconstruction and navigation systems. While temporal inte- gration would enable more accurate reconstruction, this would carry the computational burden of handling topological changes due to occlusion phenomena. We successfully tested our system in a challenging urban scenario along a large loop using an omnidirectional camera mounted on the roof of a car.

Scalable Dense Large-Scale Mapping and Navigation

PRETTO, ALBERTO;MENEGATTI, EMANUELE
2010

Abstract

This paper describes a scalable dense 3D recon- struction and navigation system suitable for real-time operation. The system represents the environment as the back-projection of a Delaunay triangulation of the omnidirectional image, estimated at each instant from two adjacent views. The cost being minimized (i.e., the reprojection error) is photometric rather than geometric, as in the majority of feature-based reconstruction and navigation systems. While temporal inte- gration would enable more accurate reconstruction, this would carry the computational burden of handling topological changes due to occlusion phenomena. We successfully tested our system in a challenging urban scenario along a large loop using an omnidirectional camera mounted on the roof of a car.
Proceedings of the 2nd. Workshop on Omnidirectional Robot Vision
9788895872025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2419857
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