Jijo-2: An Office Robot that Communicates and Learns
IEEE Intelligent Systems
A Robust PCA Algorithm for Building Representations from Panoramic Images
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Iconic Memory-Based Omnidirectional Route Panorama Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Omnidirectional Vision Based Topological Navigation
International Journal of Computer Vision
Panoramic Localization in the 4-Legged League
RoboCup 2006: Robot Soccer World Cup X
Toward Image-Based Localization for AIBO Using Wavelet Transform
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
A framework for robust and incremental self-localization of a mobile robot
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Image similarity based on Discrete Wavelet Transform for robots with low-computational resources
Robotics and Autonomous Systems
Robotics and Autonomous Systems
Bubble space and place representation in topological maps
International Journal of Robotics Research
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The results of recent studies on the possibility of spatial localization from panoramic images have shown good prospects for view-based methods. The major advantages of these methods are a wide field-of-view, capability of modeling cluttered environments, and flexibility in the learning phase. The redundant information captured in similar views is efficiently handled by the eigenspace approach. However, the standard approaches are sensitive to noise and occlusion. In this paper, we present a method of view-based localization in a robust framework that solves these problems to a large degree. Experimental results on a large set of real panoramic images demonstrate the effectiveness of the approach and the level of achieved robustness.