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Identifying Objects in Range Data Based on Similarity Transformation Invariant Shape Signatures

Published

Author(s)

Xiaolan Li, Asim Wagan, Afzal A. Godil

Abstract

Identification and recognition of three dimensional (3D) objects in range data is a challenging problem. We propose a novel method to fulfill the task through two steps: 1) construct the feature signatures for the objects in the scene and the models in a 3D database; 2) based on the feature signature, find out the most similar model which decides the class of the corresponding object in the scene. We also evaluate the accuracy, robustness of the recognition method with several configurations. Our experimental results validate the effectiveness of our method.
Conference Dates
August 19-21, 2008
Conference Location
Gaithersburg, MD
Conference Title
Performance Metrics for Intelligent Systems Workshop Proceedings (PerMIS)

Keywords

accuracy evaluation, object recognition

Citation

Li, X. , Wagan, A. and Godil, A. (2008), Identifying Objects in Range Data Based on Similarity Transformation Invariant Shape Signatures, Performance Metrics for Intelligent Systems Workshop Proceedings (PerMIS), Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=890022 (Accessed May 26, 2024)

Issues

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Created August 19, 2008, Updated February 19, 2017