Improving Visual Object Tracking Using General UFIR and Kalman Filters Under Disturbances in Bounding Boxes

Improving Visual Object Tracking Using General UFIR and Kalman Filters Under Disturbances in Bounding Boxes

A well-known problem of visual object tracking is the difficulty of accurately estimating the object trajectory under conditions of environmental disturbances in the bounding box (BB) of a video camera. In this paper, we consider BB variations as Gaussian-Markov colored measurement noise (CMN). In o...

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Bibliographic Details
Main Authors: Eli G. Pale-Ramon, Luis J. Morales-Mendoza, Mario Gonzalez-Lee, Oscar G. Ibarra-Manzano, Jorge A. Ortega-Contreras, Yuriy S. Shmaliy
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Visual object tracking
bounding box
environmental disturbance
colored measurement noise
general UFIR filter
general Kalman filter
Online Access:https://ieeexplore.ieee.org/document/10136713/

Internet

https://ieeexplore.ieee.org/document/10136713/

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