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Incremental Version Space Merging Approach to 3D Object Model Acquisition for Robot Vision

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Challenges in Automation, Robotics and Measurement Techniques (ICA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 440))

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Abstract

A concept learning algorithm is developed, which uses the visual information generated by a virtual receptor in a robotic system (e.g. symbolic image segments) to create learning examples. Its goal is to detect similarities in the training data and to create an appropriate object model. The version-space, intended to describe the possible concept hypotheses, is generated by a novel IVSM-ID algorithm, the incremental version space merging with imperfect data, that deals with partly imperfect and noisy training data—a common problem in computer vision systems. The generated model takes the form of a graph of constraints with fuzzy predicates. The approach is verified by learning concepts of elementary surface and solid primitives on base of segmented RGB-D images, taken for various light conditions and for different exposure times.

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Acknowledgments

The authors gratefully acknowledge the support of the National Centre for Research and Development (Poland), grant no. PBS1/A3/8/2012.

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Authors and Affiliations

  1. Institute of Control and Computation Engineering, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Jan Figat & Włodzimierz Kasprzak

Authors
  1. Jan Figat
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  2. Włodzimierz Kasprzak
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Correspondence to Jan Figat .

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Editors and Affiliations

  1. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Roman Szewczyk

  2. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Cezary Zieliński

  3. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Małgorzata Kaliczyńska

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Figat, J., Kasprzak, W. (2016). Incremental Version Space Merging Approach to 3D Object Model Acquisition for Robot Vision. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Challenges in Automation, Robotics and Measurement Techniques. ICA 2016. Advances in Intelligent Systems and Computing, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-29357-8_49

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  • DOI: https://doi.org/10.1007/978-3-319-29357-8_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29356-1

  • Online ISBN: 978-3-319-29357-8

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