Proceedings Article10.1109/WISP.2007.4447564
Monocular SLAM for Visual Odometry
Rodrigo Munguia,Antoni Grau +1 more
- 01 Oct 2007
- pp 1-6
53
TL;DR: Monocular simultaneous localization and mapping techniques implicitly estimate camera ego-motion while incrementally build a map of the environment while maintaining frame rate operation becomes impractical in monocular SLAM.
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Abstract: The ego-motion online estimation process from a video input is often called visual odometry. Typically optical flow and structure from motion (SFM) techniques have been used for visual odometry. Monocular simultaneous localization and mapping (SLAM) techniques implicitly estimate camera ego-motion while incrementally build a map of the environment. However in monocular SLAM, when the number of features in the system state increases, the computational cost grows rapidly; consequently maintaining frame rate operation becomes impractical. In this paper monocular SLAM is proposed for map-based visual odometry. The number of features is bounded removing features dynamically from the system state, for maintaining a stable processing time. In the other hand if features are removed then previous visited sites can not be recognized, nevertheless in an odometry context this could not be a problem. A method for feature initialization and a simple method for recovery metric scale are proposed. The experimental results using real image sequences show that the scheme presented in this paper is promising.
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Citations
Walking and Running on Yielding and Fluidizing Ground
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- 09 Jul 2012
TL;DR: Presented at Robotics: Science and Systems VIII, July 09-July 13, 2012, University of Sydney, Sydney, NSW, Australia.
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Review of visual odometry: types, approaches, challenges, and applications
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Visual 3-D SLAM from UAVs
Jorge Artieda,José M. Sebastián,Pascual Campoy,Juan F. Correa,Iván F. Mondragón,Carol Martinez,Miguel Olivares +6 more
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Visual map matching and localization using a global feature map
Oliver Pink
- 23 Jun 2008
TL;DR: This paper presents a novel method to support environmental perception of mobile robots by the use of a global feature map that allows for estimating the robot position at a higher precision than by a purely GPS-based localization, while at the same time providing information about the environment far beyond the current field of view.
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TL;DR: This work presents a top-down Bayesian framework for single-camera localisation via mapping of a sparse set of natural features using motion modelling and an information-guided active measurement strategy, in particular addressing the difficult issue of real-time feature initialisation via a factored sampling approach.
•Proceedings Article
Visual odometry
David Nister,Oleg Naroditsky,James R. Bergen +2 more
- 01 Jan 2004
TL;DR: A system that estimates the motion of a stereo head or a single moving camera based on video input in real-time with low delay and the motion estimates are used for navigational purposes.
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Unified Inverse Depth Parametrization for Monocular SLAM
J. M. M. Montiel,Javier Civera,Andrew J. Davison +2 more
- 16 Aug 2006
TL;DR: This paper presents a new unified parametrization for point features within monocular SLAM which permits efficient and accurate representation of uncertainty during undelayed initialisation and beyond, all within the standard EKF (Extended Kalman Filter).
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Real-time 3d SLAM with wide-angle vision
TL;DR: This work presents the first real-time (30 frames per second), fully automatic implementation of 3D SLAM using a hand-waved wide-angle camera, and demonstrates significant advances in the range and agility of motions which can be tracked over previous narrow field-of-view implementations.
233
A Robust Visual Odometry and Precipice Detection System Using Consumer-grade Monocular Vision
Jason Campbell,Rahul Sukthankar,Illah Nourbakhsh,A. Pahwa +3 more
- 18 Apr 2005
TL;DR: A monocular robot vision system which accomplishes accurate 3-DOF dead-reckoning, closed loop motion control, and precipice and obstacle detection, all in dynamic environments, using a single, consumer-grade web cam and typical laptop computer hardware.
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