A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Monocular visual odometry based on hybrid parameterization
Tekijät: Sherif A. S. Mohamed, Mohammad-Hashem Haghbayan, Jukka Heikkonen, Hannu Tenhunen, Juha Plosila
Toimittaja: Wolfgang Osten, Dmitry P. Nikolaev
Konferenssin vakiintunut nimi: International Conference on Machine Vision
Kustantaja: SPIE
Julkaisuvuosi: 2020
Journal: International Conference on Machine Vision
Kokoomateoksen nimi: Twelfth International Conference on Machine Vision (ICMV 2019)
Tietokannassa oleva lehden nimi: Proceedings of SPIE - The International Society for Optical Engineering
Sarjan nimi: Proceedings of SPIE : the International Society for Optical Engineering
Vuosikerta: 11433
Sivujen määrä: 6
ISSN: 0277-786X
DOI: https://doi.org/10.1117/12.2556718
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/46944484
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.
Ladattava julkaisu This is an electronic reprint of the original article. |