Robust Feature Extraction and Matching for Omnidirectional Images

Abstract : This paper presents a new and robust method for extracting and match- ing visual vertical features between images taken by an omnidirectional camera. Matching robustness is achieved by creating a descriptor which is unique and dis- tinctive for each feature. Furthermore, the proposed descriptor is invariant to ro- tation. The robustness of the approach is validated through real experiments with a wheeled robot equipped with an omnidirectional camera. We show that vertical lines are very well extracted and tracked during the robot motion. At the end, we also present an application of our algorithm to the robot simultaneous localization and mapping in an unknown environment.
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https://hal.inria.fr/inria-00200862
Contributor : Agostino Martinelli <>
Submitted on : Friday, December 21, 2007 - 4:33:43 PM
Last modification on : Tuesday, April 2, 2019 - 2:03:11 AM
Long-term archiving on : Thursday, September 27, 2012 - 1:20:17 PM

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Davide Scaramuzza, Nicolas Criblez, Agostino Martinelli, Roland Siegwart. Robust Feature Extraction and Matching for Omnidirectional Images. 6th International Conference on Field and Service Robotics - FSR 2007, Jul 2007, Chamonix, France. ⟨inria-00200862⟩

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