Illumination Planning for Object Recognition Using Parametric Eigenspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of 3D objects in cluttered scenes using hierarchical eigenspace
Pattern Recognition Letters
EM algorithms for PCA and SPCA
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Robust recognition using eigenimages
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Early Visual Learning
Understanding Intelligence
Catadioptric Projective Geometry
International Journal of Computer Vision
Proceedings of the International Workshop on Object Representation in Computer Vision II
ECCV '96 Proceedings of the International Workshop on Object Representation in Computer Vision II
A Robust PCA Algorithm for Building Representations from Panoramic Images
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Robust Localization Using Eigenspace of Spinning-Images
OMNIVIS '00 Proceedings of the IEEE Workshop on Omnidirectional Vision
Robust Localization Using Panoramic View-Based Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Cognitive vision: The case for embodied perception
Image and Vision Computing
Swarm-supported outdoor localization with sparse visual data
Robotics and Autonomous Systems
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In this contribution we present a framework for an embodied robotic system that is capable of appearance-based self-localization. Specifically, we concentrate on the issues of robustness, flexibility, and scalability of the system. The framework presented is based on a panoramic eigenspace model of the environment. Its main feature is that it allows for simultaneous localization and map building using an incremental learning algorithm. Further, both the learning and the training processes are designed in a way to achieve robustness and adaptability to changes in the environment.