IEEE Transactions on Pattern Analysis and Machine Intelligence
Discrete cosine transform: algorithms, advantages, applications
Discrete cosine transform: algorithms, advantages, applications
Solutions and Ambiguities of the Structure and Motion Problem for 1DRetinal Vision
Journal of Mathematical Imaging and Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Moment invariants for recognition under changing viewpoint and illumination
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Wide-Baseline Stereo Matching with Line Segments
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
IEEE Transactions on Robotics
Vision-based global localization and mapping for mobile robots
IEEE Transactions on Robotics
Panoramic appearance-based recognition of video contents using matching graphs
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
International Journal of Robotics Research
Efficient data association for view based SLAM using connected dominating sets
Robotics and Autonomous Systems
Autonomous navigation of vehicles from a visual memory using a generic camera model
IEEE Transactions on Intelligent Transportation Systems
Visual control through the trifocal tensor for nonholonomic robots
Robotics and Autonomous Systems
Improving topological maps for safer and robust navigation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Self-location from monocular uncalibrated vision using reference omniviews
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Topological maps based on graphs of planar regions
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Efficiently searching for similar images
Communications of the ACM
Omnidirectional visual control of mobile robots based on the 1D trifocal tensor
Robotics and Autonomous Systems
Mapping and Localization for Mobile Robots through Environment Appearance Update
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Distributed multi-camera visual mapping using topological maps of planar regions
Pattern Recognition
Global localization with non-quantized local image features
Robotics and Autonomous Systems
Robotics and Autonomous Systems
Bubble space and place representation in topological maps
International Journal of Robotics Research
Robust omnidirectional mobile robot topological navigation system using omnidirectional vision
Engineering Applications of Artificial Intelligence
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We propose a new vision-based method for global robot localization using an omnidirectional camera. Topological and metric localization information are combined in an efficient, hierarchical process, with each step being more complex and accurate than the previous one but evaluating fewer images. This allows us to work with large reference image sets in a reasonable amount of time. Simultaneously, thanks to the use of 1D three-view geometry, accurate metric localization can be achieved based on just a small number of nearby reference images. Owing to the wide baseline features used, the method deals well with illumination changes and occlusions, while keeping the computational load small. The simplicity of the radial line features used speeds up the process without affecting the accuracy too much. We show experiments with two omnidirectional image data sets to evaluate the performance of the method and compare the results using the proposed radial lines with results from state-of-the-art wide-baseline matching techniques.