A Bayesian Filter for Multi-View 3D Multi-Object Tracking With Occlusion Handling

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A Bayesian Filter for Multi-View 3D Multi-Object Tracking With Occlusion Handling

This paper proposes an online multi-camera multi-object tracker that only requires monocular detector training, independent of the multi-camera configurations, allowing seamless extension/deletion of cameras without retraining effort. The proposed algorithm has a linear complexity in the total numbe...

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Bibliographic Details
Main Authors:	Ong, Jonah, Vo, Ba Tuong, Vo, Ba-Ngu, Kim, Du Yong, Nordholm, Sven
Format:	Journal Article
Language:	English
Published:	IEEE COMPUTER SOC 2022
Subjects:	Science & Technology Technology Computer Science, Artificial Intelligence Engineering, Electrical & Electronic Computer Science Engineering Three-dimensional displays Cameras Trajectory Bayes methods Detectors Training Visualization Multi-view multi-sensor multi-object visual tracking occlusion handling generalized labeled multi-bernoulli PERFORMANCE EVALUATION MULTITARGET TRACKING VISUAL TRACKING CAMERAS
Online Access:	http://purl.org/au-research/grants/arc/DP170104854 http://hdl.handle.net/20.500.11937/90801

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