Title | A Bayesian Solution to Robustly Track Multiple Objects from Visual Data |
Publication Type | Book Chapter |
Año de publicación | 2008 |
Autores | Marron, M, Garcia, JC, Sotelo, MA, Pizarro, D, Bravo, I, Martin, JL |
Book Title | INTELLIGENT TECHNIQUES AND TOOLS FOR NOVEL SYSTEM ARCHITECTURES |
Series Title | Studies in Computational Intelligence |
Volumen | 109 |
Páginas | 531-547 |
Fecha de publicación | 09/2008 |
Editorial | Springer-Verlag. |
City | Berlin/Heidelberg (ALEMANIA) |
Idioma de publicación | English |
Numero ISBN | 978-3-540-77621-5 |
Palabras clave | artificial vision, bayesian estimation, Multi-Object Tracking |
Abstract | Different solutions have been proposed for multiple objects tracking based on probabilistic algorithms. In this chapter, the authors propose the use of a single particle filter to track a variable number of objects in a complex environment. |
Resumen | Different solutions have been proposed for multiple objects tracking based on probabilistic algorithms. In this chapter, the authors propose the use of a single particle filter to track a variable number of objects in a complex environment. |
URL | http://www.springer.com/engineering/mathematical/book/978-3-540-77621-5 |
DOI | 10.1007/978-3-540-77623-9_30 |
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a_bayesian_solution-fulltext.pdf | 618.34 KB |