Scene Understanding and 3D Imagination: A Comparison between Machine Learning and Human Cognition

Michael Schoosleitner, Torsten Ullrich

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spatial perception and three-dimensional imagination are important characteristics for many construction tasks in civil engineering. In order to support people in these tasks, worldwide research is being carried out on assistance systems based on machine learning and augmented reality. In this paper, we examine the machine learning component and compare it to human performance. The test scenario is to recognize a partly-assembled model, identify its current status, i.e. the current instruction step, and to return the next step. Thus, we created a database of 2D images containing the complete set of instruction steps of the corresponding 3D model. Afterwards, we trained the deep neural network RotationNet with these images. Usually, the machine learning approaches are compared to each other; our contribution evaluates the machine learning results with human performance tested in a survey: in a clean-room setting the survey and RotationNet results are comparable and neither is significa ntly better. The real-world results show that the machine learning approaches need further improvements
Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Computer Vision and Computer Graphics Theory and Applications
EditorsManuela Chessa, Alexis Paljic, Jose Braz
PublisherSciTePress
Pages231-238
Number of pages8
Volume2, HUCAPP
ISBN (Electronic)978-989-758-402-2
DOIs
Publication statusPublished - 2020
Event16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications: VISIGRAPP 2021 - Virtuell, Austria
Duration: 8 Feb 202110 Feb 2021

Publication series

NameVISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Volume2

Conference

Conference16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
CountryAustria
CityVirtuell
Period8/02/2110/02/21

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