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Robust Perception for Aerial Inspection: Adaptive and On-Line Techniques

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Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 129)

Abstract

This chapter explains an adaptive on-line object detection and classification technique for robust perception due to varying scene conditions, for example partial cast shadows, change on the illumination conditions or changes in the angle of the object target view. This approach continuously updates the target model upon arrival of new data, being able to adapt to dynamic situations. The method uses an on-line learning technique that works on real-time and it is continuously updated in order to adapt to potential changes undergone by the target object. The method can run in real-time.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Idiap Research InstituteMartignySwitzerland
  2. 2.CSIC-UPC, Institut de Robòtica i Informàtica IndustrialBarcelonaSpain

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