Spatial-visual label propagation for local feature classification

Tarek El-Gaaly, Marwan Torki, Ahmed Elgammal

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

1 Scopus citations

Abstract

In this paper we present a novel approach to integrate feature similarity and spatial consistency of local features to achieve the goal of localizing an object of interest in an image. The goal is to achieve coherent and accurate labeling of feature points in a simple and effective way. We introduced our Spatial-Visual Label Propagation algorithm to infer the labels of local features in a test image from known labels. This is done in a transductive manner to provide spatial and feature smoothing over the learned labels. We show the value of our novel approach by a diverse set of experiments with successful improvements over previous methods and baseline classifiers.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3422-3427
Number of pages6
ISBN (Electronic)9781479952083
DOIs
StatePublished - Dec 4 2014
Event22nd International Conference on Pattern Recognition, ICPR 2014 - Stockholm, Sweden
Duration: Aug 24 2014Aug 28 2014

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Other

Other22nd International Conference on Pattern Recognition, ICPR 2014
CountrySweden
CityStockholm
Period8/24/148/28/14

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Spatial-visual label propagation for local feature classification'. Together they form a unique fingerprint.

Cite this