Chapter

Computer Vision – ECCV 2008

Volume 5305 of the series Lecture Notes in Computer Science pp 102-115

CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching

  • Motilal AgrawalAffiliated withSRI International
  • , Kurt KonoligeAffiliated withWillow Garage
  • , Morten Rufus BlasAffiliated withElektro/DTU University

* Final gross prices may vary according to local VAT.

Get Access

Abstract

We explore the suitability of different feature detectors for the task of image registration, and in particular for visual odometry, using two criteria: stability (persistence across viewpoint change) and accuracy (consistent localization across viewpoint change). In addition to the now-standard SIFT, SURF, FAST, and Harris detectors, we introduce a suite of scale-invariant center-surround detectors (CenSurE) that outperform the other detectors, yet have better computational characteristics than other scale-space detectors, and are capable of real-time implementation.