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Evaluation of 3D Interest Point Detection Techniques via Human-generated Ground Truth

Published

Author(s)

Afzal A. Godil, Helin Dutagaci

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

Keywords

3D Interest Points, 3D Salient Points, 3D Shape Analysis

Citation

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 May 20, 2024)

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