Probabilistic Egomotion for Stereo Visual Odometry
Probabilistic Egomotion for Stereo Visual Odometry
dc.contributor.author | Hugo Miguel Silva | en |
dc.contributor.author | Bernardino,A | en |
dc.contributor.author | Eduardo Silva | en |
dc.date.accessioned | 2018-01-10T15:27:01Z | |
dc.date.available | 2018-01-10T15:27:01Z | |
dc.date.issued | 2015 | en |
dc.description.abstract | We present a novel approach of Stereo Visual Odometry for vehicles equipped with calibrated stereo cameras. We combine a dense probabilistic 5D egomotion estimation method with a sparse keypoint based stereo approach to provide high quality estimates of vehicle's angular and linear velocities. To validate our approach, we perform two sets of experiments with a well known benchmarking dataset. First, we assess the quality of the raw velocity estimates in comparison to classical pose estimation algorithms. Second, we added to our method's instantaneous velocity estimates a Kalman Filter and compare its performance with a well known open source stereo Visual Odometry library. The presented results compare favorably with state-of-the-art approaches, mainly in the estimation of the angular velocities, where significant improvements are achieved. | en |
dc.identifier.uri | http://repositorio.inesctec.pt/handle/123456789/5882 | |
dc.identifier.uri | http://dx.doi.org/10.1007/s10846-014-0054-5 | en |
dc.language | eng | en |
dc.relation | 5429 | en |
dc.relation | 5570 | en |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.title | Probabilistic Egomotion for Stereo Visual Odometry | en |
dc.type | article | en |
dc.type | Publication | en |
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