Robust Multi-Object Tracking: A Labeled Random Finite Set Approach
| dc.contributor.author | Gardiyawasam Punchihewa, Yuthika Samanmali | |
| dc.contributor.supervisor | Ba-Ngu Vo | en_US |
| dc.date.accessioned | 2019-07-16T06:07:55Z | |
| dc.date.available | 2019-07-16T06:07:55Z | |
| dc.date.issued | 2018 | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/75844 | |
| dc.description.abstract |
The labeled random finite set based generalized multi-Bernoulli filter is a tractable analytic solution for the multi-object tracking problem. The robustness of this filter is dependent on certain knowledge regarding the multi-object system being available to the filter. This dissertation presents techniques for robust tracking, constructed upon the labeled random finite set framework, where complete information regarding the system is unavailable. | en_US |
| dc.publisher | Curtin University | en_US |
| dc.title | Robust Multi-Object Tracking: A Labeled Random Finite Set Approach | en_US |
| dc.type | Thesis | en_US |
| dcterms.educationLevel | PhD | en_US |
| curtin.department | School of Electrical Engineering, Computing and Mathematical Sciences | en_US |
| curtin.accessStatus | Open access | en_US |
| curtin.faculty | Science and Engineering | en_US |