Abstract
Scene understanding is still an important challenge in robotics. Nevertheless scene recognition involves determining when an image is good enough to represent the scene and therefore it can be used for classification. Most research on scene recognition involves working with sets of images which have been acquired using a predefined sampling rate, nevertheless, this means working with very noisy and redundant sets of images. In this paper we analyse different alternatives to automatically select images according to amount of information they provide and how representative they are.
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Acknowledgment
This work was supported by grants: GPC2013/040 (FEDER), TIN2012-32262.
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Santos-Saavedra, D., Pardo, X.M., Iglesias, R. (2015). Canonical Views for Scene Recognition in Mobile Robotics. In: Paredes, R., Cardoso, J., Pardo, X. (eds) Pattern Recognition and Image Analysis. IbPRIA 2015. Lecture Notes in Computer Science(), vol 9117. Springer, Cham. https://doi.org/10.1007/978-3-319-19390-8_58
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DOI: https://doi.org/10.1007/978-3-319-19390-8_58
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