Convolutional Unscented Kalman Filter for Multi-Object Tracking With Outliers

S. H. Liu; Wenhan Cao; Chang Liu; Tianyi Zhang; Shengbo Eben Li

doi:10.1109/tiv.2024.3446851

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JOURNAL ARTICLE

Convolutional Unscented Kalman Filter for Multi-Object Tracking With Outliers

S. H. Liu Wenhan Cao Chang Liu Tianyi Zhang Shengbo Eben Li

Year: 2024 Journal: IEEE Transactions on Intelligent Vehicles Vol: 10 (5)Pages: 3113-3123 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tiv.2024.3446851

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Keywords:

Kalman filter Artificial intelligence Outlier Computer vision Computer science Video tracking Tracking (education) Object (grammar) Convolutional neural network Pattern recognition (psychology) Psychology

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Target Tracking and Data Fusion in Sensor Networks

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Measurement and Detection Methods

Physical Sciences → Engineering → Electrical and Electronic Engineering

Convolutional Unscented Kalman Filter for Multi-Object Tracking With Outliers

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