Naslov
Large scale vision based navigation without an accurate global reconstruction

Autori
Šegvić, Siniša ; Remazeilles, Anthony ; Diosi, Albert ; Chaumette, François

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Computer Vision and Pattern Recognition, June 18-23, 2007, Minneapolis, MN / Takeo Kanade, Gerard Medioni - : Institute of Electrical and Electronics Engineers (IEEE), 2007

ISBN
1-4244-1180-7

Skup
IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Mjesto i datum
Minneapolis (MN), Sjedinjene Američke Države, 18.06.2007. - 23.06.2007

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Autonomous navigation

Sažetak
Autonomous cars will likely play an important role in the future. A vision system designed to support outdoor navigation for such vehicles has to deal with large dynamic environments, changing imaging conditions, and temporary occlusions by other moving objects. This paper presents a novel appearance-based navigation framework relying on a single perspective vision sensor, which is aimed towards resolving of the above issues. The solution is based on a hierarchical environment representation created during a teaching stage, when the robot is controlled by a human operator. At the top level, the representation contains a graph of key-images with extracted 2D features enabling a robust navigation by visual servoing. The information stored at the bottom level enables to efficiently predict the locations of the features which are currently not visible, and eventually (re-)start their tracking. The outstanding property of the proposed framework is that it enables robust and scalable navigation without requiring a globally consistent map, even in interconnected environments. This result has been confirmed by realistic off-line experiments and successful real-time navigation trials in public urban areas.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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