Neural physics simulation through volumetric reconstruction
Name
1192560823-MIT.pdf
Size
1.96 MB
Format
Adobe PDF
Checksum (MD5)
6d4553b340691d760f9668847d41827c
Author(s)
Ho, Helen(Helen W.)
Advisor(s)
Frédo Durand.
Date Issued
2020
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis we propose a method for simulating 3D object motion given 2D image input or simplified 3D models. Our system incorporates neural networks for tasks that are otherwise complex or computationally expensive to model realistically, such as 3D reconstruction and force calculations, and utilizes a physics-based integration step system to simulate object motion over time using the outputs of these neural networks. We detail the components of the system, evaluate some of our architecture decisions, explore its performance with various input data and network parameters, and propose future extensions.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 37-39).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
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