A method to quantify a descriptor's illumination variance

Ross, Patrick, English, Andrew, Ball, David, & Corke, Peter (2014) A method to quantify a descriptor's illumination variance. In Australian Conference on Robotics and Automation (ACRA 2014), 2-4 December 2014, University of Melbourne, Melbourne, VIC.

View at publisher (open access)


This paper presents a new metric, which we call the lighting variance ratio, for quantifying descriptors in terms of their variance to illumination changes. In many applications it is desirable to have descriptors that are robust to changes in illumination, especially in outdoor environments. The lighting variance ratio is useful for comparing descriptors and determining if a descriptor is lighting invariant enough for a given environment. The metric is analysed across a number of datasets, cameras and descriptors. The results show that the upright SIFT descriptor is typically the most lighting invariant descriptor.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

59 since deposited on 05 Mar 2015
20 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 82218
Item Type: Conference Paper
Refereed: Yes
Divisions: Current > Research Centres > ARC Centre of Excellence for Robotic Vision
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 [Please consult the Authors]
Deposited On: 05 Mar 2015 23:08
Last Modified: 09 Mar 2015 04:37

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page