Book Chapter10.1007/3-540-30292-1_20
Visual Odometry Using Sparse Bundle Adjustment on an Autonomous Outdoor Vehicle
Niko Sünderhauf,Niko Sünderhauf,Kurt Konolige,Kurt Konolige,Simon Lacroix,Simon Lacroix,Peter Protzel,Peter Protzel +7 more
- 01 Dec 2006
- pp 157-163
75
TL;DR: In this article, a visual odometry approach using a specialized method of sparse bundle adjustment is presented, which is a feasible method for estimating motion in unstructured outdoor environments, without prior knowledge of the scene nor the motion is necessary.
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Abstract: Visual Odometry is the process of estimating the movement of a (stereo) camera through its environment by matching point features between pairs of consecutive image frames. No prior knowledge of the scene nor the motion is necessary. In this work, we present a visual odometry approach using a specialized method of sparse bundle adjustment. We show experimental results that proof our approach to be a feasible method for estimating motion in unstructured outdoor environments.
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Citations
Visual Odometry [Tutorial]
TL;DR: Visual odometry is the process of estimating the egomotion of an agent (e.g., vehicle, human, and robot) using only the input of a single or If multiple cameras attached to it, and application domains include robotics, wearable computing, augmented reality, and automotive.
1.6K
SBA: A software package for generic sparse bundle adjustment
TL;DR: Sba as mentioned in this paper is a C/C++ software package for generic bundle adjustment with high efficiency and flexibility regarding parameterization, which can be used to achieve considerable computational savings when applied to bundle adjustment.
Large-Scale Visual Odometry for Rough Terrain
Kurt Konolige,Motilal Agrawal,Joan Sola +2 more
- 01 Jan 2010
TL;DR: Using data with ground truth from an RTK GPS system, it is shown experimentally that the algorithms can track motion, in off-road terrain, over distances of 10 km, with an error of less than 10 m.
Interior construction state recognition with 4D BIM registered image sequences
TL;DR: A novel method that increases the degree of automation for indoor progress monitoring by recognizing the actual state of construction activities from as-built video data based on as-planned BIM data using computer vision algorithms.
140
Automated sparse 3D point cloud generation of infrastructure using its distinctive visual features
Habib Fathi,Ioannis Brilakis +1 more
TL;DR: An automated stereo vision-based method, as an alternative and inexpensive solution, to producing a sparse Euclidean 3D point cloud of an infrastructure scene utilizing two video streams captured by a set of two calibrated cameras.
102
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- 01 Jan 1988
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