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Description
  • Local feature detectors and descriptors are widelyused in many computer vision applications and various methods have been proposed during the past decade. There have been a number of evaluations focused on various aspects of local features, matching accuracy in particular, however there has been no comparisons considering the accuracy and speed trade-offs of recent extractors such as BRIEF, BRISK, ORB, MRRID, MROGH and LIOP. This paper provides a performance evaluation of recent feature detectors and compares their matching precision and speed in randomized kdtrees setup as well as an evaluation of binary descriptors with efficient computation of Hamming distance.
  • Local feature detectors and descriptors are widelyused in many computer vision applications and various methods have been proposed during the past decade. There have been a number of evaluations focused on various aspects of local features, matching accuracy in particular, however there has been no comparisons considering the accuracy and speed trade-offs of recent extractors such as BRIEF, BRISK, ORB, MRRID, MROGH and LIOP. This paper provides a performance evaluation of recent feature detectors and compares their matching precision and speed in randomized kdtrees setup as well as an evaluation of binary descriptors with efficient computation of Hamming distance. (en)
Title
  • Evaluation of Local Detectors and Descriptors for Fast Feature Matching
  • Evaluation of Local Detectors and Descriptors for Fast Feature Matching (en)
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  • Evaluation of Local Detectors and Descriptors for Fast Feature Matching
  • Evaluation of Local Detectors and Descriptors for Fast Feature Matching (en)
skos:notation
  • RIV/68407700:21230/12:00200382!RIV13-GA0-21230___
http://linked.open...avai/riv/aktivita
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  • P(GBP103/12/G084)
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  • 135128
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  • RIV/68407700:21230/12:00200382
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  • Features and Image Descriptors; Low-Level Vision; Vision for Robotics (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [0D1C388E3514]
http://linked.open...v/mistoKonaniAkce
  • Tsukuba
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • ICPR 2012: Proceedings of 21st International Conference on Pattern Recognition
http://linked.open...in/vavai/riv/obor
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  • Mikolajczyk, K.
  • Mikšík, Ondřej
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http://linked.open.../riv/zahajeniAkce
number of pages
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  • IEEE
https://schema.org/isbn
  • 978-4-9906441-0-9
http://localhost/t...ganizacniJednotka
  • 21230
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