Planar Object Tracking via Weighted Optical Flow
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00371649" target="_blank" >RIV/68407700:21230/23:00371649 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/WACV56688.2023.00164" target="_blank" >https://doi.org/10.1109/WACV56688.2023.00164</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/WACV56688.2023.00164" target="_blank" >10.1109/WACV56688.2023.00164</a>
Alternative languages
Result language
angličtina
Original language name
Planar Object Tracking via Weighted Optical Flow
Original language description
We propose WOFT - a novel method for planar object tracking that estimates a full 8 degrees-of-freedom pose, i.e. the homography w.r.t. a reference view. The method uses a novel module that leverages dense optical flow and assigns a weight to each optical flow correspondence, estimating a homography by weighted least squares in a fully differentiable manner. The trained module assigns zero weights to incorrect correspondences (outliers) in most cases, making the method robust and eliminating the need of the typically used non-differentiable robust estimators like RANSAC. The proposed weighted optical flow tracker (WOFT) achieves state-of-the-art performance on two benchmarks, POT-210 [23] and POIC [7], tracking consistently well across a wide range of scenarios.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proc. of the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
ISBN
978-1-6654-9346-8
ISSN
2472-6737
e-ISSN
2642-9381
Number of pages
10
Pages from-to
1593-1602
Publisher name
IEEE
Place of publication
Piscataway
Event location
Waikoloa
Event date
Jan 3, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000971500201067