Pedestrian Tracking with Monocular Camera using Unconstrained 3D Motion Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43973069" target="_blank" >RIV/49777513:23520/24:43973069 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.23919/FUSION59988.2024.10706432" target="_blank" >https://doi.org/10.23919/FUSION59988.2024.10706432</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/FUSION59988.2024.10706432" target="_blank" >10.23919/FUSION59988.2024.10706432</a>
Alternative languages
Result language
angličtina
Original language name
Pedestrian Tracking with Monocular Camera using Unconstrained 3D Motion Model
Original language description
A first-principle single-object model is proposed for pedestrian tracking. It is assumed that the extent of the moving object can be described via known statistics in 3D, such as pedestrian height. The proposed model thus need not constrain the object motion in 3D to a common ground plane, which is usual in 3D visual tracking applications. A nonlinear filter for this model is implemented using the unscented Kalman filter (UKF) and tested using the publicly available MOT-17 dataset. The proposed solution yields promising results in 3D while maintaining excellent results when projected into the 2D image. Moreover, the estimation error covariance matches the true one. Unlike conventional methods, the introduced model parameters have convenient meaning and can readily be adjusted for a problem.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
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 27th International Conference on Information Fusion (FUSION)
ISBN
978-1-73774-976-9
ISSN
—
e-ISSN
—
Number of pages
8
Pages from-to
—
Publisher name
IEEE
Place of publication
Venice
Event location
Venice, Italy
Event date
Jul 7, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001334560000160