Robust Multi-Object Tracking: A Labeled Random Finite Set Approach
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 t...
| Main Author: | |
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| Format: | Thesis |
| Published: |
Curtin University
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/75844 |
| _version_ | 1848763599311339520 |
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| author | Gardiyawasam Punchihewa, Yuthika Samanmali |
| author_facet | Gardiyawasam Punchihewa, Yuthika Samanmali |
| author_sort | Gardiyawasam Punchihewa, Yuthika Samanmali |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:06:01Z |
| format | Thesis |
| id | curtin-20.500.11937-75844 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:06:01Z |
| publishDate | 2018 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-758442019-07-16T06:07:55Z Robust Multi-Object Tracking: A Labeled Random Finite Set Approach Gardiyawasam Punchihewa, Yuthika Samanmali 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. 2018 Thesis http://hdl.handle.net/20.500.11937/75844 Curtin University fulltext |
| spellingShingle | Gardiyawasam Punchihewa, Yuthika Samanmali Robust Multi-Object Tracking: A Labeled Random Finite Set Approach |
| title | Robust Multi-Object Tracking: A Labeled Random Finite Set Approach |
| title_full | Robust Multi-Object Tracking: A Labeled Random Finite Set Approach |
| title_fullStr | Robust Multi-Object Tracking: A Labeled Random Finite Set Approach |
| title_full_unstemmed | Robust Multi-Object Tracking: A Labeled Random Finite Set Approach |
| title_short | Robust Multi-Object Tracking: A Labeled Random Finite Set Approach |
| title_sort | robust multi-object tracking: a labeled random finite set approach |
| url | http://hdl.handle.net/20.500.11937/75844 |