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S2CMAF: Multi-Method Assessment Fusion for Scan-to-CAD Methods

  • Technical University of Munich
  • Siemens AG

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Scan-to-CAD-based 3D reconstruction of indoor environments has become increasingly more popular in recent years. The inherent structure of Scan-to-CAD consists of object detection, model retrieval, and alignment. Therefore, a variety of metrics are required to assess these three aspects. This can lead to ambiguous evaluation results and incorrect quality assumptions. To impede the problem of incorrect evaluation, we introduce S2CMAF, a multi-method assessment fusion approach for Scan-to-CAD pipelines. S2CMAF merges several metrics used in evaluating these pipelines into one unique quality score. We show that S2CMAF significantly improves the correlation between Scan-to-CAD results and the ground truth, compared to the conventionally used Scan2CAD benchmark. Additionally, we train S2CMAF using different optimization techniques and demonstrate the advantages of our approach on real-world data.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Symposium on Multimedia, ISM 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages129-136
Number of pages8
ISBN (Electronic)9781665471725
DOIs
StatePublished - 2022
Event24th IEEE International Symposium on Multimedia, ISM 2022 - Virtual, Online, Italy
Duration: 5 Dec 20227 Dec 2022

Publication series

NameProceedings - 2022 IEEE International Symposium on Multimedia, ISM 2022

Conference

Conference24th IEEE International Symposium on Multimedia, ISM 2022
Country/TerritoryItaly
CityVirtual, Online
Period5/12/227/12/22

Keywords

  • 3D Data
  • Evaluation
  • Metric
  • Multi-Method Assessment Fusion
  • Quality Assessment
  • Scan-to-CAD

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