Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Simultaneous Localization and Map-Building Using Active Vision
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Object Recognition from Local Scale-Invariant Features
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Selection of Scale-Invariant Parts for Object Class Recognition
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Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving simultaneous mapping and localization in 3D using global constraints
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Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters
IEEE Transactions on Robotics
Using Local Symmetry for Landmark Selection
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Real-time optical SLAM-based mosaicking for unmanned underwater vehicles
Intelligent Service Robotics
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In this paper we present several interest points detectors and we analyze their suitability when used as landmark extractors for vision-based simultaneous localization and mapping (vSLAM). For this purpose, we evaluate the detectors according to their repeatability under changes in viewpoint and scale. These are the desired requirements for visual landmarks. Several experiments were carried out using sequence of images captured with high precision. The sequences represent planar objects as well as 3D scenes.