Godil, A.
and Dutagaci, H.
(2012),
Evaluation of 3D Interest Point Detection Techniques via Human-generated Ground Truth, Visual Computer, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=911521
(Accessed September 10, 2024)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Evaluation of 3D Interest Point Detection Techniques via Human-generated Ground Truth
Published
Author(s)
,
Abstract
In this paper, we present an evaluation strategy based on human-generated ground truth to measure the performance of 3D interest point detection techniques. We provide quantitative evaluation measures that relate automatically detected interest points to human-marked points, which were collected through a web-based application. We give visual demonstrations and a discussion on the results of the subjective experiments. We use a voting-based method to construct ground truth for 3D models and propose three evaluation measures, namely False Positive and False Negative Errors, and Weighted Miss Error to compare interest point detection algorithms.Citation
Visual Computer
Pub Type
Journals
Download Paper
Keywords
3D Interest Points, 3D Salient Points, 3D Shape Analysis
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.
Created June 29, 2012, Updated February 19, 2017