A4 Vertaisarvioitu artikkeli konferenssijulkaisussa

Monocular visual odometry based on hybrid parameterization




TekijätSherif A. S. Mohamed, Mohammad-Hashem Haghbayan, Jukka Heikkonen, Hannu Tenhunen, Juha Plosila

ToimittajaWolfgang Osten, Dmitry P. Nikolaev

Konferenssin vakiintunut nimiInternational Conference on Machine Vision

KustantajaSPIE

Julkaisuvuosi2020

JournalInternational Conference on Machine Vision

Kokoomateoksen nimiTwelfth International Conference on Machine Vision (ICMV 2019)

Tietokannassa oleva lehden nimiProceedings of SPIE - The International Society for Optical Engineering

Sarjan nimiProceedings of SPIE : the International Society for Optical Engineering

Vuosikerta11433

Sivujen määrä6

ISSN0277-786X

DOIhttps://doi.org/10.1117/12.2556718

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/46944484


Tiivistelmä

Visual odometry (VO) is one of the most challenging techniques in computer vision for autonomous vehicle/vessels. In VO, the camera pose that also represents the robot pose in ego-motion is estimated analyzing the features and pixels extracted from the camera images. Different VO techniques mainly provide different trade-offs among the resources that are being considered for odometry, such as camera resolution, computation/communication capacity, power/energy consumption, and accuracy. In this paper, a hybrid technique is proposed for camera pose estimation by combining odometry based on triangulation using the long-term period of direct-based odometry and the short-term period of inverse depth mapping. Experimental results based on the EuRoC data set shows that the proposed technique significantly outperforms the traditional direct-based pose estimation method for Micro Aerial Vehicle (MAV), keeping its potential negative effect on performance negligible.


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Last updated on 2024-26-11 at 13:27