Comparison of key point detectors in SIFT implementation for mobile devices

  • Authors:
  • Karol Matusiak;Piotr Skulimowski

  • Affiliations:
  • Institute of Electronics, Technical University of Lodz, Poland;Institute of Electronics, Technical University of Lodz, Poland

  • Venue:
  • ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
  • Year:
  • 2012

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Abstract

The paper presents a comparison of key point selection methods used for recognition of objects in scenes recorded by a built-in mobile phone camera. The detected key points include corners and line crossings. An application for Android smartphones was developed utilizing the Features from Accelerated Segment Test (FAST) and Scale-Invariant Feature Transform (SIFT), which was specially modified for processing low resolution images. The implemented algorithm computes descriptors which are invariant to image acquisition settings such as: rotation, noise, scale and brightness variations. The proposed image classification algorithm is based on pairing key points based on similarity of their descriptors.