CSDD features

Center-surround distribution distance for feature extraction and matching

Robert Collins, Weina Ge

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

We present an interest region operator and feature descriptor called Center-Surround Distribution Distance (CSDD) that is based on comparing feature distributions between a central foreground region and a surrounding ring of background pixels. In addition to finding the usual light(dark) blobs surrounded by a dark(light) background, CSDD also detects blobs with arbitrary color distribution that "stand out" perceptually because they look different from the background. A proof-of-concept implementation using an isotropic scale-space extracts feature descriptors that are invariant to image rotation and covariant with change of scale. Detection repeatability is evaluated and compared with other state-of-the-art approaches using a standard dataset, while use of CSDD features for image registration is demonstrated within a RANSAC procedure for affine image matching.

Original languageEnglish (US)
Title of host publicationComputer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings
Pages140-153
Number of pages14
Volume5304 LNCS
EditionPART 3
DOIs
StatePublished - 2008
Event10th European Conference on Computer Vision, ECCV 2008 - Marseille, France
Duration: Oct 12 2008Oct 18 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume5304 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th European Conference on Computer Vision, ECCV 2008
CountryFrance
CityMarseille
Period10/12/0810/18/08

Fingerprint

Distance Distribution
Distribution Center
Feature Matching
Feature Extraction
Feature extraction
Descriptors
Image matching
Image registration
RANSAC
Image Matching
Scale Space
Pixels
Repeatability
Image Registration
Color
Pixel
Ring
Invariant
Arbitrary
Operator

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Collins, R., & Ge, W. (2008). CSDD features: Center-surround distribution distance for feature extraction and matching. In Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings (PART 3 ed., Vol. 5304 LNCS, pp. 140-153). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5304 LNCS, No. PART 3). https://doi.org/10.1007/978-3-540-88690-7-11
Collins, Robert ; Ge, Weina. / CSDD features : Center-surround distribution distance for feature extraction and matching. Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings. Vol. 5304 LNCS PART 3. ed. 2008. pp. 140-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).
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Collins, R & Ge, W 2008, CSDD features: Center-surround distribution distance for feature extraction and matching. in Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings. PART 3 edn, vol. 5304 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 5304 LNCS, pp. 140-153, 10th European Conference on Computer Vision, ECCV 2008, Marseille, France, 10/12/08. https://doi.org/10.1007/978-3-540-88690-7-11

CSDD features : Center-surround distribution distance for feature extraction and matching. / Collins, Robert; Ge, Weina.

Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings. Vol. 5304 LNCS PART 3. ed. 2008. p. 140-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5304 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Collins R, Ge W. CSDD features: Center-surround distribution distance for feature extraction and matching. In Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings. PART 3 ed. Vol. 5304 LNCS. 2008. p. 140-153. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). https://doi.org/10.1007/978-3-540-88690-7-11