Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exploring artificial intelligence in the new millennium
Landmark Identification Based on Projective and Permutation Invariant Vectors
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Autonomous navigation of vehicles from a visual memory using a generic camera model
IEEE Transactions on Intelligent Transportation Systems
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Motion planning for maintaining landmarks visibility with a differential drive robot
Robotics and Autonomous Systems
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This article describes visual functions dedicated to the extraction and recognition of visual landmarks, here planar quadrangles detected by a single camera. Landmarks are extracted among edge segments through a relaxation scheme, used to apply geometrical, topological and appearance constraints on sets of segments. Once extracted, such a landmark is characterized by invariant attributes so that recognition is made possible from a large range of viewpoints. Landmarks are represented by an icon which is built using the homography between the current viewpoint and a reference shape (a square). When detected again, the landmark is recognized by using a distance between icons. We propose a comparison of several of these metrics and an evaluation on actual and synthetic images that shows the validity of our approach. Results issued from experiments of a mobile robot navigating in an indoor environment are finally presented.