Learning non-rigid surface reconstruction from spatio-temporal image patches |
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Author: | Pedone, Matteo1; Mostafa, Abdelrahman1; Heikkilä, Janne1 |
Organizations: |
1Center for Machine Vision Research and Signal Analysis, University of Oulu, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 2.7 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2021102151933 |
Language: | English |
Published: |
IEEE Computer Society,
2021
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Publish Date: | 2021-10-21 |
Description: |
AbstractWe present a method to reconstruct a dense spatiotemporal depth map of a non-rigidly deformable object directly from a video sequence. The estimation of depth is performed locally on spatio-temporal patches of the video, and then the full depth video of the entire shape is recovered by combining them together. Since the geometric complexity of a local spatiotemporal patch of a deforming non-rigid object is often simple enough to be faithfully represented with a parametric model, we artificially generate a database of small deforming rectangular meshes rendered with different material properties and light conditions, along with their corresponding depth videos, and use such data to train a convolutional neural network. We tested our method on both synthetic and Kinect data and experimentally observed that the reconstruction error is significantly lower than the one obtained using conventional non-rigid structure from motion approaches. see all
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Series: |
International Conference on Pattern Recognition |
ISSN: | 1051-4651 |
ISSN-L: | 1051-4651 |
ISBN: | 978-1-7281-8808-9 |
ISBN Print: | 978-1-7281-8809-6 |
Pages: | 10134 - 10140 |
DOI: | 10.1109/ICPR48806.2021.9412352 |
OADOI: | https://oadoi.org/10.1109/ICPR48806.2021.9412352 |
Host publication: |
2020 25th International Conference on Pattern Recognition (ICPR) |
Conference: |
International Conference on Pattern Recognition |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Copyright information: |
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