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In this paper the authors compare the behavior of different interest points detectors and descriptors under the conditions needed to be used as landmarks in vision-based Simultaneous Localization And Mapping (SLAM). The authors evaluate the repeatability of the detectors, as well as the invariance and distinctiveness of the descriptors, under different perceptual conditions using sequences of images representing planar objects as well as 3D scenes. They believe that this information will be useful when selecting an appropriate landmark detector and descriptor for visual SLAM.
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