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

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...

Full description

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

Internet

http://purl.org/au-research/grants/arc/DP170104854
http://hdl.handle.net/20.500.11937/90801

Similar Items