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2008

Unsupervised identification of useful visual landmarks using multiple segmentations and top-down feedback

8 years 11 months ago
Unsupervised identification of useful visual landmarks using multiple segmentations and top-down feedback
In this paper, we tackle the problem of unsupervised selection and posterior recognition of visual landmarks in images sequences acquired by an indoor mobile robot. This is a highly valuable perceptual capability for a wide variety of robotic applications, in particular autonomous navigation. Our method combines a bottom-up data driven approach with top-down feedback provided by high level semantic representations. The bottom-up approach is based on three main mechanisms: visual attention, area segmentation, and landmark characterization. As there is no segmentation method that works properly in every situation, we integrate multiple segmentation algorithms in order to increase the robustness of the approach. In terms of the top-down feedback, this is provided by two information sources: i) An estimation of the robot position that reduces the searching scope for potential matches with previously selected landmarks, ii) A set of weights that, according to the results of previous recogn...
Pablo Espinace, Daniel Langdon, Alvaro Soto
Added 28 Dec 2010
Updated 28 Dec 2010
Type Journal
Year 2008
Where RAS
Authors Pablo Espinace, Daniel Langdon, Alvaro Soto
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