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Towards semantic SLAM using a monocular camera | IEEE Conference Publication | IEEE Xplore

Towards semantic SLAM using a monocular camera


Abstract:

Monocular SLAM systems have been mainly focused on producing geometric maps just composed of points or edges; but without any associated meaning or semantic content. In t...Show More

Abstract:

Monocular SLAM systems have been mainly focused on producing geometric maps just composed of points or edges; but without any associated meaning or semantic content. In this paper, we propose a semantic SLAM algorithm that merges in the estimated map traditional meaningless points with known objects. The non-annotated map is built using only the information extracted from a monocular image sequence. The known object models are automatically computed from a sparse set of images gathered by cameras that may be different from the SLAM camera. The models include both visual appearance and tridimensional information. The semantic or annotated part of the map -the objects- are estimated using the information in the image sequence and the precomputed object models.
Date of Conference: 25-30 September 2011
Date Added to IEEE Xplore: 05 December 2011
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Conference Location: San Francisco, CA, USA

References

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