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Computer vision aided navigation systems

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Computer vision aided navigation systems. / Davidson, P.; Merkulova, I.

23rd Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2016 - Proceedings. State Research Center of the Russian Federation, 2016. s. 560-562.

Tutkimustuotosvertaisarvioitu

Harvard

Davidson, P & Merkulova, I 2016, Computer vision aided navigation systems. julkaisussa 23rd Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2016 - Proceedings. State Research Center of the Russian Federation, Sivut 560-562, SAINT PETERSBURG INTERNATIONAL CONFERENCE ON INTEGRATED NAVIGATION SYSTEMS, 1/01/00.

APA

Davidson, P., & Merkulova, I. (2016). Computer vision aided navigation systems. teoksessa 23rd Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2016 - Proceedings (Sivut 560-562). State Research Center of the Russian Federation.

Vancouver

Davidson P, Merkulova I. Computer vision aided navigation systems. julkaisussa 23rd Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2016 - Proceedings. State Research Center of the Russian Federation. 2016. s. 560-562

Author

Davidson, P. ; Merkulova, I. / Computer vision aided navigation systems. 23rd Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2016 - Proceedings. State Research Center of the Russian Federation, 2016. Sivut 560-562

Bibtex - Lataa

@inproceedings{5e736c4a13a54ed1875d9383977a1392,
title = "Computer vision aided navigation systems",
abstract = "The paper considers the possible use of computer vision systems for INS aiding. Two methods of navigation data obtaining from the image sequence are analyzed. The first method uses the features of architectural elements in indoor and urban conditions for generation of object attitude parameters. The second method is based on extraction of general features in the image and is more widely applied. Besides the orientation parameters, the second method estimates the object displacement, and thus can be used as visual odometry technique. The described algorithms can be used to develop small-sized MEMS navigation systems efficiently operating in urban conditions.",
keywords = "Camera, Computer vision, Data fusion, Image processing, Inertial system, Orientation",
author = "P. Davidson and I. Merkulova",
year = "2016",
language = "English",
pages = "560--562",
booktitle = "23rd Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2016 - Proceedings",
publisher = "State Research Center of the Russian Federation",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Computer vision aided navigation systems

AU - Davidson, P.

AU - Merkulova, I.

PY - 2016

Y1 - 2016

N2 - The paper considers the possible use of computer vision systems for INS aiding. Two methods of navigation data obtaining from the image sequence are analyzed. The first method uses the features of architectural elements in indoor and urban conditions for generation of object attitude parameters. The second method is based on extraction of general features in the image and is more widely applied. Besides the orientation parameters, the second method estimates the object displacement, and thus can be used as visual odometry technique. The described algorithms can be used to develop small-sized MEMS navigation systems efficiently operating in urban conditions.

AB - The paper considers the possible use of computer vision systems for INS aiding. Two methods of navigation data obtaining from the image sequence are analyzed. The first method uses the features of architectural elements in indoor and urban conditions for generation of object attitude parameters. The second method is based on extraction of general features in the image and is more widely applied. Besides the orientation parameters, the second method estimates the object displacement, and thus can be used as visual odometry technique. The described algorithms can be used to develop small-sized MEMS navigation systems efficiently operating in urban conditions.

KW - Camera

KW - Computer vision

KW - Data fusion

KW - Image processing

KW - Inertial system

KW - Orientation

UR - http://www.scopus.com/inward/record.url?scp=84979499890&partnerID=8YFLogxK

M3 - Conference contribution

SP - 560

EP - 562

BT - 23rd Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2016 - Proceedings

PB - State Research Center of the Russian Federation

ER -