NDLI: Monocular visual odometry in urban environments using an omnidirectional camera

Content Provider	IEEE Xplore Digital Library
Author	Tardif, J.-P. Pavlidis, Y. Daniilidis, K.
Copyright Year	2008
Description	Author affiliation: GRASP Lab., Univ. of Pennsylvania, Philadelphia, PA (Tardif, J.-P.; Pavlidis, Y.; Daniilidis, K.)
Abstract	We present a system for monocular simultaneous localization and mapping (mono-SLAM) relying solely on video input. Our algorithm makes it possible to precisely estimate the camera trajectory without relying on any motion model. The estimation is completely incremental: at a given time frame, only the current location is estimated while the previous camera positions are never modified. In particular, we do not perform any simultaneous iterative optimization of the camera positions and estimated 3D structure (local bundle adjustment). The key aspect of the system is a fast and simple pose estimation algorithm that uses information not only from the estimated 3D map, but also from the epipolar constraint. We show that the latter leads to a much more stable estimation of the camera trajectory than the conventional approach. We perform high precision camera trajectory estimation in urban scenes with a large amount of clutter. Using an omnidirectional camera placed on a vehicle, we cover one of the longest distance ever reported, up to 2.5 kilometers.
Starting Page	2531
Ending Page	2538
File Size	813338
Page Count	8
File Format	PDF
ISBN	9781424420575
DOI	10.1109/IROS.2008.4651205
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three dimensional displays Cameras Estimation Robustness Tracking Vehicles Robot sensing systems
Content Type	Text
Resource Type	Article

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