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Recent Advances in Feature Detectors and Descriptors: A Survey

  • Lee, Haeseong ;
  • Jeon, Semi ;
  • Yoon, Inhye ;
  • Paik, Joonki
  • Received : 2016.04.05
  • Accepted : 2016.06.08
  • Published : 2016.06.30

Abstract

Local feature extraction methods for images and videos are widely applied in the fields of image understanding and computer vision. However, robust features are detected differently when using the latest feature detectors and descriptors because of diverse image environments. This paper analyzes various feature extraction methods by summarizing algorithms, specifying properties, and comparing performance. We analyze eight feature extraction methods. The performance of feature extraction in various image environments is compared and evaluated. As a result, the feature detectors and descriptors can be used adaptively for image sequences captured under various image environments. Also, the evaluation of feature detectors and descriptors can be applied to driving assistance systems, closed circuit televisions (CCTVs), robot vision, etc.

Keywords

Keypoints;Feature detection;Feature description;Image matching;Invariant features;Computational cost

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Cited by

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  2. Continuous digital zooming of asymmetric dual camera images using registration and variational image restoration pp.1573-0824, 2017, https://doi.org/10.1007/s11045-017-0534-4
  3. Robust Video Stabilization Using Particle Keypoint Update and l1-Optimized Camera Path vol.17, pp.2, 2017, https://doi.org/10.3390/s17020337

Acknowledgement

Grant : Development of global multi-target tracking and event prediction techniques based on real-time large-scale video analysis

Supported by : Institute for Information & communications Technology Promotion(IITP)