Adaptive Kalman Filter for Real-Time Visual Object Tracking Based on Autocovariance Least Square Estimation

Adaptive Kalman Filter for Real-Time Visual Object Tracking Based on Autocovariance Least Square Estimation

Real-time visual object tracking (VOT) may suffer from performance degradation and even divergence owing to inaccurate noise statistics typically engendered by non-stationary video sequences or alterations in the tracked object. This paper presents a novel adaptive Kalman filter (AKF) algorithm, ter...

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Bibliographic Details
Main Authors: Jiahong Li, Xinkai Xu, Zhuoying Jiang, Beiyan Jiang
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Applied Sciences
Subjects:
visual object tracking
Kalman filter
autocovariance least-squares estimation
background subtraction
adaptive thresholding
Online Access:https://www.mdpi.com/2076-3417/14/3/1045

Internet

https://www.mdpi.com/2076-3417/14/3/1045

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