Pedestrian Tracking with Monocular Camera: Simple 2D Filter Springing From 3D Modeling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43973068" target="_blank" >RIV/49777513:23520/24:43973068 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/MFI62651.2024.10705764" target="_blank" >https://doi.org/10.1109/MFI62651.2024.10705764</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/MFI62651.2024.10705764" target="_blank" >10.1109/MFI62651.2024.10705764</a>
Alternative languages
Result language
angličtina
Original language name
Pedestrian Tracking with Monocular Camera: Simple 2D Filter Springing From 3D Modeling
Original language description
A simple and real-time 2D single-object visual tracker is derived based on first-principle modeling in 3D, which was introduced in previous work. An inverse of the nonlinear perspective projection is followed by a simple approximation assuming that the pedestrian moves with a fixed depth in front of the camera. The resulting 2D tracking algorithm appears to have a similar form as the state-of-the-art single-object tracker from BoT-SORT, is easy to implement, and its parameters have convenient meaning. Its performance is assessed statistically using the publicly available MOT17 dataset.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotics and advanced industrial production</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
ISBN
979-8-3503-6803-1
ISSN
2835-947X
e-ISSN
2767-9357
Number of pages
6
Pages from-to
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Publisher name
IEEE
Place of publication
Plzeň
Event location
Plzeň, Česká republika
Event date
Sep 4, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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