Advanced data association techniques in multi-target tracking system | Solving to multi-target tracking issues. Cet article n’est pas disponible.
Langue : anglais
Edité par LAP LAMBERT Academic Publishing, 2012
- Livre broché
- Neuf

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A propos de cet article
Advanced data association techniques in multi-target tracking system | Solving to multi-target tracking issues | Negm Eldin Mohamed Shawky (u. a.) | Taschenbuch | 212 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659306938 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
N° de réf. du vendeur 106154104
- Titre
- Advanced data association techniques in multi-target tracking system | Solving to multi-target tracking issues
- Auteur
- Negm Eldin Mohamed Shawky (u. a.)
- Éditeur
- LAP LAMBERT Academic Publishing
- Année de publication
- 2012
- État de l'article
- Neu
- Reliure
- Taschenbuch
- Langue
- anglais
- ISBN à 10 chiffres
- 3659306932
- ISBN à 13 chiffres
- 9783659306938
- Poids de l'article
- 334 grammes
- Dimensions
- 220 x 150 x 14 mm
- Catalogues du vendeur
- Bücher
In multi-target tracking system, data association and tracking filter are two basic parts of tracking objects. The choosing of data association technique to associate the track to the true target in noisy received measurements is an important key to overcome the issues of the tracking process. Many data association algorithms have been developed to be the most powerful techniques for these issues, but still there are disadvantages in their restricting assumptions, complexity and in the resulting performance. For these reasons, some of data association algorithms that are widely used have been studied. These algorithms have some issues during tracking in dense clutter environment, tracking a highly maneuvering targets and swapping in the presence of more background clutter and false signal. Then, these algorithms have been updated to overcome the issues, improve the performance, decrease the burden of the computational cost, decrease the probability of error and to give the targets the ability to continue tracking without failing.
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