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national Conference on Intelligent Robots and Sys-
tems. IEEE,Aug2005.
[20] C. McCarthy, N. Barnes, and R. Mahony. A robust
docking strategy for a mobile robot using flow field
divergence. IEEE Transactions on Robotics, 24(4),
Aug2008.
[21] M.A.MehralianandM.Soryani. Ekfpnp: Extended
kalman filter for camera pose estimation in a se-
quenceofimages. arXivpreprintarXiv:1906.10324,
2019.
[22] J. Moras, V. Cherfaoui, and P. Bonnifait. A lidar
perceptionschemefor intelligentvehiclenavigation.
In 2010 11th International Conference on Control
Automation Robotics & Vision, pages 1809–1814.
IEEE,2010.
[23] M. Oberweger, P. Wohlhart, and V. Lepetit. Hands
deep in deep learning for hand pose estimation.
arXivpreprintarXiv:1502.06807, 2015.
[24] G.Pavlakos,X.Zhou,A.Chan,K.G.Derpanis, and
K. Daniilidis. 6-dof object pose from semantic key-
points. In 2017 IEEE International Conference on
RoboticsandAutomation (ICRA). IEEE,2017.
[25] M. Persson and K. Nordberg. Lambda twist: an
accurate fast robust perspective three point (p3p)
solver. In Proceedings of the European Conference
onComputer Vision.ECCV,2018.
[26] S. Ren, K. He, R. B. Girshick, and J. Sun. Faster R-
CNN:towardsreal-timeobjectdetectionwithregion
proposalnetworks. CoRR, abs/1506.01497,2015.
[27] F. J. Romero-Ramirez, R. Mun˜oz-Salinas, and
R. Medina-Carnicer. Speeded up detection of
squared fiducial markers. Image and vision Com-
puting, 76,2018.
[28] J. Ro¨weka¨mper, C. Sprunk, G. D. Tipaldi, C. Stach-
niss, P. Pfaff, and W. Burgard. On the position ac-
curacy of mobile robot localization based on parti-
cle filters combined with scan matching. In 2012
IEEE/RSJ International Conference on Intelligent
RobotsandSystems, pages3158–3164. IEEE,2012.
[29] G. Schweighofer and A. Pinz. Globally optimal o
(n) solution to the pnp problem for general camera
models. InProceedingsof the2008BritishMachine
VisionConference.BMVC,2008.
[30] E. Shalnov and A. Konushin. Convolutional neural
network for camera pose estimation from object de-
tections. International Archives of the Photogram-
metry, Remote Sensing & Spatial Information Sci-
ences, 42,2017.
[31] R. Siegwart, I. R. Nourbakhsh, and D. Scaramuzza.
Autonomousmobile robots. MITpress, 2011.
[32] S. Thrun, W. Burgard, and D. Fox. Probabilistic
robotics. MITPress, 2002.
[33] B. Triggs. Camera pose and calibration from 4 or
5 known 3d points. In Proceedings of the Seventh
IEEEInternationalConferenceonComputerVision,
volume1,pages 278–284. IEEE,1999. [34] E. Yurtsever, J. Lambert, A. Carballo, and
K. Takeda. A survey of autonomous driving: Com-
mon practices and emerging technologies. arXiv
preprintarXiv:1906.05113, 2019.
[35] X. Zhou, D. Wang, and P. Kra¨henbu¨hl. Objects as
points. CoRR, abs/1904.07850,2019.
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Joint Austrian Computer Vision and Robotics Workshop 2020
- Titel
- Joint Austrian Computer Vision and Robotics Workshop 2020
- Herausgeber
- Graz University of Technology
- Ort
- Graz
- Datum
- 2020
- Sprache
- englisch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-85125-752-6
- Abmessungen
- 21.0 x 29.7 cm
- Seiten
- 188
- Kategorien
- Informatik
- Technik