Abstract
An appearance-based approach for visual mapping and localization is proposed in this paper. On the one hand, a new image similarity measure between images based on number of matchings and their associated distances is introduced. On the other hand, to optimize running times, matchings between the current image and previous visited places are determined using an index based on a set of randomized KD-trees. Further, a discrete Bayes filter is used for predicting loop candidates, taking into account the previous relationships between visual locations. The approach has been validated using image sequences from several environments. Whereas most other approaches use omnidirectional cameras, a single-view configuration has been selected for our experiments.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Zivkovic, Z., Bakker, B., Krose, B.: Hierarchical Map Building Using Visual Landmarks and Geometric Constraints. In: International Conference on Intelligent Robots and Systems, pp. 2480–2485 (2005)
Ulrich, I., Nourbakhsh, I.: Appearance-Based Place Recognition for Topological Localization. In: International Conference on Robotics and Automation, pp. 1023–1029 (2000)
Goedemé, T., Nuttin, M., Tuytelaars, T., Van Gool, L.: Markerless Computer Vision Based Localization using Automatically Generated Topological Maps. In: European Navigation Conference, pp. 235–243 (2004)
Sabatta, D.G.: Vision-based Topological Map Building and Localisation using Persistent Features. In: Robotics and Mechatronics Symposium (2008)
Cummins, M., Newman, P.: FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance. International Journal of Robotics Research 27(6), 647–665 (2008)
Angeli, A., Doncieux, S., Meyer, J.A., Filliat, D.: Incremental Vision-Based Topological SLAM. In: International Conference on Intelligent Robots and Systems, pp. 22–26 (2008)
Angeli, A., Doncieux, S., Meyer, J.A., Filliat, D.: Real-Time Visual Loop-Closure Detection. In: International Conference on Robotics and Automation, pp. 1842–1847 (2008)
Zhang, H.: Indexing Visual Features: Real-Time Loop Closure Detection Using a Tree Structure. In: International Conference on Robotics and Automation, pp. 3613–3618 (2012)
Sivic, J., Zisserman, A.: Video Google: A Text Retrieval Approach to Object Matching in Videos. In: International Conference on Computer Vision, pp. 1470–1477 (2003)
Zhang, H.: BoRF: Loop-Closure Detection with Scale Invariant Visual Features. In: International Conference on Robotics and Automation, pp. 3125–3130 (2011)
Oliva, A., Torralba, A.: Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope. International Journal of Computer Vision 42(3), 145–175 (2001)
Singh, G., Kosecka, J.: Visual Loop Closing using Gist Descriptors in Manhattan World. In: International Conference on Robotics and Automation (2010)
Liu, Y., Zhang, H.: Visual Loop Closure Detection with a Compact Image Descriptor. In: International Conference on Intelligent Robots and Systems, pp. 1051–1056 (2012)
Kawewong, A., Tongprasit, N., Tungruamsub, S., Hasegawa, O.: Online and Incremental Appearance-Based SLAM in Highly Dynamic Environments. International Journal of Robotics Research 30(1), 33–55 (2011)
Zhang, H., Li, B., Yang, D.: Keyframe Detection for Appearance-Based Visual SLAM. In: International Conference on Intelligent Robots and Systems, pp. 2071–2076 (2010)
Bay, H., Tuytelaars, T., Van Gool, L.: SURF: Speeded Up Robust Features. Computer Vision and Image Understanding 3951(3), 404–417 (2006)
Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Garcia-Fidalgo, E., Ortiz, A. (2013). Probabilistic Appearance-Based Mapping and Localization Using Visual Features. In: Sanches, J.M., Micó, L., Cardoso, J.S. (eds) Pattern Recognition and Image Analysis. IbPRIA 2013. Lecture Notes in Computer Science, vol 7887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38628-2_33
Download citation
DOI: https://doi.org/10.1007/978-3-642-38628-2_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38627-5
Online ISBN: 978-3-642-38628-2
eBook Packages: Computer ScienceComputer Science (R0)