Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/7270
Título: Probabilistic Egomotion for Stereo Visual Odometry
Autor: Silva, Hugo
Bernardino, A.
Silva, Eduardo
Palavras-chave: Stereo vision
Visual Odometry
Egomotion
Visual Navigation
Data: 2015
Editora: Springer
Relatório da Série N.º: Journal of Intelligent & Robotic Systems;Vol. 77, Issue 2
Resumo: 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.
URI: http://hdl.handle.net/10400.22/7270
DOI: 10.1007/s10846-014-0054-5
ISSN: 1573-0409
Versão do Editor: http://link.springer.com/article/10.1007/s10846-014-0054-5
Aparece nas colecções:ISEP – LSA – Artigos

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