Performances of Invariant Feature Detectors in Real-Time Video Applications

  • M. Hedayati
  • W. Mimi Diyana
  • W. Zaki
  • Aini Hussain
  • Mohd. Asyraf Zulkifley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8237)


This paper reviews and compares the performance of five well-known detectors, SIFT, SURF, ORB, MSER and STAR, when combined in combination of with using three common descriptors, SIFT, SURF and ORB. To validate the results, these descriptors’ performances are verified using three scenarios that differ with respect to changes in scale, light variation and rotation. The results show that the SIFT and SURF detectors possess the most stable features, with an overall accuracy of 80% under various conditions. Among the tested descriptors, SURF provides the best description of each keypoint.




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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • M. Hedayati
    • 1
  • W. Mimi Diyana
    • 1
  • W. Zaki
    • 1
  • Aini Hussain
    • 1
  • Mohd. Asyraf Zulkifley
    • 1
  1. 1.Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaMalaysia

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