Year: 2010
Type: conference-paper
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. I.
Institutions: University of Padua, University of California, Los Angeles
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2317730969