View-Based Robot Localization Using Illumination-Invariant Spherical Harmonics Descriptors
نویسندگان
چکیده
In this work we present a view-based approach for robot self-localization using a hemispherical camera system. We use view descriptors that are based upon Spherical Harmonics as orthonormal basis functions on the sphere. The resulting compact representation of the image signal enables us to efficiently compare the views taken at different locations. With the view descriptors stored in a database, we compute a similarity map for the current view by means of a suitable distance metric. Advanced statistical models based upon principal component analysis introduced to that metric allows to deal with severe illumination changes, extending our method to real-world applications.
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View-Based Robot Localization Using Spherical Harmonics: Concept and First Experimental Results
Robot self-localization using a hemispherical camera system can be done without correspondences. We present a view-based approach using view descriptors, which enables us to efficiently compare the image signal taken at different locations. A compact representation of the image signal can be computed using Spherical Harmonics as orthonormal basis functions defined on the sphere. This is particu...
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