About: Novel descriptors of keypoints are proposed for matching (primarily) biological images. The descriptors incorporate characteristics of limited-size neighborhoods of keypoints. Descriptors are quantized into small vocabularies representing photometry of images (SIFT words) and geometry of their neighborhoods, so that significant distortions can be tolerated. In order to keep precision at a high level, Harris-Affine and Hessian-Affine detectors are independently applied. The retrieval results are accepted only if confirmed by both techniques. Using several test datasets, we preliminarily show that the method can retrieve semantically meaningful data from unknown and unpredictable images without any training or supervision. Low computational complexity of the method makes it a good candidate for scalable analysis of biological (e.g. zoological or botanical) visual databases.   Goto Sponge  NotDistinct  Permalink

An Entity of Type : fabio:Abstract, within Data Space : covidontheweb.inria.fr associated with source document(s)

AttributesValues
type
value
  • Novel descriptors of keypoints are proposed for matching (primarily) biological images. The descriptors incorporate characteristics of limited-size neighborhoods of keypoints. Descriptors are quantized into small vocabularies representing photometry of images (SIFT words) and geometry of their neighborhoods, so that significant distortions can be tolerated. In order to keep precision at a high level, Harris-Affine and Hessian-Affine detectors are independently applied. The retrieval results are accepted only if confirmed by both techniques. Using several test datasets, we preliminarily show that the method can retrieve semantically meaningful data from unknown and unpredictable images without any training or supervision. Low computational complexity of the method makes it a good candidate for scalable analysis of biological (e.g. zoological or botanical) visual databases.
Subject
  • Geometry
  • Feature detection (computer vision)
  • Computational complexity theory
  • Analysis of algorithms
  • Object recognition and categorization
part of
is abstract of
is hasSource of
Faceted Search & Find service v1.13.91 as of Mar 24 2020


Alternative Linked Data Documents: Sponger | ODE     Content Formats:       RDF       ODATA       Microdata      About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data]
OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software