Proceedings ArticleDOI
Robust place recognition using local appearance based methods
Gregory Dudek,D. Jugessur +1 more
- Vol. 2, pp 1030-1035
TLDR
The approach is to learn visual features in the appearance domain that can be used to characterize an object or a location using single camera images that are defined statistically and then recognized using principal components in the frequency domain.Abstract:
We present an approach to the automatic recognition of locations or landmarks using single camera images Our approach is to learn visual features in the appearance domain that can be used to characterize an object or a location These features are defined statistically and then are recognized using principal components in the frequency domain We show that this technique can be used to recognize specific objects on varying backgrounds, as well as environmental featuresread more
Citations
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Journal ArticleDOI
Appearance-only SLAM at large scale with FAB-MAP 2.0
Mark Cummins,Paul Newman +1 more
TL;DR: A new formulation of appearance-only SLAM suitable for very large scale place recognition that incorporates robustness against perceptual aliasing and substantially outperforms the standard term-frequency inverse-document-frequency (tf-idf) ranking measure.
Proceedings ArticleDOI
Unified loop closing and recovery for real time monocular SLAM
Ethan Eade,Tom Drummond +1 more
TL;DR: A unified method for recovering from tracking failure and closing loops in real time monocular simultaneous localisation and mapping, and a bag-of-words appearance model for ranking potential loop closures and a robust method for using both structure and image appearance to confirm likely matches.
Journal ArticleDOI
Unsupervised learning to detect loops using deep neural networks for visual SLAM system
Xiang Gao,Tao Zhang +1 more
TL;DR: The results show that SDA is feasible for detecting loops at a satisfactory precision and can therefore provide an alternative way for visual SLAM systems and show the workflow of training the network, utilizing the features and computing the similarity score.
Proceedings ArticleDOI
Semantic Modeling of Places using Objects
TL;DR: Presented at the 2007 Robotics: Science and Systems Conference III (RSS), 27-30 June 2007, Atlanta, GA.
Journal ArticleDOI
Bayesian inference in the space of topological maps
TL;DR: A general framework for modeling measurements is described, and the use of a Markov-chain Monte Carlo algorithm that uses specific instances of these models for odometry and appearance measurements to estimate the posterior distribution is described.
References
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Proceedings ArticleDOI
Object recognition from local scale-invariant features
TL;DR: Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.
Journal ArticleDOI
Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
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Mobile robot localization using landmarks
Margrit Betke,Leonid Gurvits +1 more
TL;DR: An efficient method for localizing a mobile robot in an environment with landmarks in which the robot can identify these landmarks and measure their bearings relative to each other is described.
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Context-free attentional operators: the generalized symmetry transform
TL;DR: An attention operator based on the intuitive notion of symmetry, which generalized many of the existing methods of detecting regions of interest is presented, a low-level operator that can be applied successfully without a priori knowledge of the world.
Journal ArticleDOI
Some location problems for robot navigation using a single camera
TL;DR: Two classes of point location problems found in visual navigation of a mobile robot are considered, finding the location of a robot using a map of the room where the robot moves and an image taken by a camera carried by the robot.