Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images
We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and trackin...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2008-02-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Online Access: | http://dx.doi.org/10.1155/2008/217373 |
| _version_ | 1818309883556003840 |
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| author | Anton G. Pavlov Rafael V. Araújo Marcelo G. S. Bruno |
| author_facet | Anton G. Pavlov Rafael V. Araújo Marcelo G. S. Bruno |
| author_sort | Anton G. Pavlov |
| collection | DOAJ |
| description | We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter. Two implementations of the proposed algorithm are discussed using, respectively, a resample-move (RS) particle filter and an auxiliary particle filter (APF). Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets. |
| first_indexed | 2024-12-13T07:37:15Z |
| format | Article |
| id | doaj.art-5821d9b348aa49c79fa27db0ffab5856 |
| institution | Directory Open Access Journal |
| issn | 1687-6172 |
| language | English |
| last_indexed | 2024-12-13T07:37:15Z |
| publishDate | 2008-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-5821d9b348aa49c79fa27db0ffab58562022-12-21T23:55:03ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61722008-02-01200810.1155/2008/217373Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar ImagesAnton G. PavlovRafael V. AraújoMarcelo G. S. BrunoWe present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter. Two implementations of the proposed algorithm are discussed using, respectively, a resample-move (RS) particle filter and an auxiliary particle filter (APF). Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets.http://dx.doi.org/10.1155/2008/217373 |
| spellingShingle | Anton G. Pavlov Rafael V. Araújo Marcelo G. S. Bruno Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images EURASIP Journal on Advances in Signal Processing |
| title | Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images |
| title_full | Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images |
| title_fullStr | Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images |
| title_full_unstemmed | Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images |
| title_short | Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images |
| title_sort | sequential monte carlo methods for joint detection and tracking of multiaspect targets in infrared radar images |
| url | http://dx.doi.org/10.1155/2008/217373 |
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