Object tracking and credal classification with kinematic data in a multi-target context
| Autor: | David Mercier, Samir Hachour, François Delmotte, Eric Lefevre |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
business.industry
Bayesian probability 020206 networking & telecommunications Context (language use) Pattern recognition Data assignment 02 engineering and technology Kinematics computer.software_genre Variety (cybernetics) Task (project management) Multi target Hardware and Architecture Video tracking Signal Processing 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Data mining business computer Software Information Systems Mathematics |
| Zdroj: | Information Fusion. 20:174-188 |
| ISSN: | 1566-2535 |
| DOI: | 10.1016/j.inffus.2014.01.007 |
| Popis: | This article proposes a method to classify multiple maneuvering targets at the same time. This task is a much harder problem than classifying a single target, as sensors do not know how to assign captured measurements to known targets. This article extends previous results scattered in the literature and unifies them in a single global framework with belief functions. Through two examples, it is shown that the full algorithm using belief functions improves results obtained with standard Bayesian classifiers and that it can be applied to a large variety of applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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