Sub-Frame Appearance and 6D Pose Estimation of Fast Moving Objects

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F20%3A00533751" target="_blank" >RIV/67985556:_____/20:00533751 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/CVPR42600.2020.00681" target="_blank" >http://dx.doi.org/10.1109/CVPR42600.2020.00681</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR42600.2020.00681" target="_blank" >10.1109/CVPR42600.2020.00681</a>

Result language
angličtina
Original language name
Sub-Frame Appearance and 6D Pose Estimation of Fast Moving Objects
Original language description
We have proposed a method for sub-frame appearance and 6D pose estimation of fast moving objects. We propose a novel method that tracks fast moving objects, mainly non-uniform spherical, in full 6 degrees of freedom, estimating simultaneously their 3D motion trajectory, 3D pose and object appearance changes with a time step that is a fraction of the video frame exposure time. The sub-frame object localization and appearance estimation allows realistic temporal super-resolution and precise shape estimation. The method, called TbD-3D (Tracking by Deblatting in 3D) relies on a novel reconstruction algorithm which solves a piece-wise deblurring and matting problem. The 3D rotation is estimated by minimizing the reprojection error. As a second contribution, we present a new challenging dataset with fast moving objects that change their appearance and distance to the camera. High-speed camera recordings with zero lag between frame exposures were used to generate videos with different frame rates annotated with ground-truth trajectory and pose.
Czech name
—
Czech description
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Project
<a href="/en/project/GA18-05360S" target="_blank" >GA18-05360S: Solving inverse problems for the analysis of fast moving objects</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
ISBN
978-1-7281-7169-2
ISSN
1063-6919
e-ISSN
2575-7075
Number of pages
9
Pages from-to
6777-6785
Publisher name
IEEE
Place of publication
Piscataway
Event location
Seattle
Event date
Jun 16, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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