Multiple target tracking in video data using labeled random finite set
This paper demonstrates how the d-Generalized Labeled Multi-Bernoulli (d-GLMB) filter can be applied to track moving targets on videos. The tracking is performed directly on the original images which are not preprocessed into point measurements and estimates the number of targets on frame along with...
| Main Authors: | , , |
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| Format: | Conference Paper |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/19812 |
| _version_ | 1848750136307482624 |
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| author | Punchihewa, Y. Papi, Francesco Hoseinnezhad, R. |
| author_facet | Punchihewa, Y. Papi, Francesco Hoseinnezhad, R. |
| author_sort | Punchihewa, Y. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper demonstrates how the d-Generalized Labeled Multi-Bernoulli (d-GLMB) filter can be applied to track moving targets on videos. The tracking is performed directly on the original images which are not preprocessed into point measurements and estimates the number of targets on frame along with their states. In that sense this concept bears resemblance to the track before detect (TBD) approach employed under low signal to noise ratio conditions. Image sequences from the CAVIAR1 dataset are used in simulations to prove the aptitude of this method. |
| first_indexed | 2025-11-14T07:32:02Z |
| format | Conference Paper |
| id | curtin-20.500.11937-19812 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:32:02Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-198122017-09-13T13:51:03Z Multiple target tracking in video data using labeled random finite set Punchihewa, Y. Papi, Francesco Hoseinnezhad, R. This paper demonstrates how the d-Generalized Labeled Multi-Bernoulli (d-GLMB) filter can be applied to track moving targets on videos. The tracking is performed directly on the original images which are not preprocessed into point measurements and estimates the number of targets on frame along with their states. In that sense this concept bears resemblance to the track before detect (TBD) approach employed under low signal to noise ratio conditions. Image sequences from the CAVIAR1 dataset are used in simulations to prove the aptitude of this method. 2015 Conference Paper http://hdl.handle.net/20.500.11937/19812 10.1109/ICCAIS.2014.7020543 Institute of Electrical and Electronics Engineers Inc. restricted |
| spellingShingle | Punchihewa, Y. Papi, Francesco Hoseinnezhad, R. Multiple target tracking in video data using labeled random finite set |
| title | Multiple target tracking in video data using labeled random finite set |
| title_full | Multiple target tracking in video data using labeled random finite set |
| title_fullStr | Multiple target tracking in video data using labeled random finite set |
| title_full_unstemmed | Multiple target tracking in video data using labeled random finite set |
| title_short | Multiple target tracking in video data using labeled random finite set |
| title_sort | multiple target tracking in video data using labeled random finite set |
| url | http://hdl.handle.net/20.500.11937/19812 |