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EnglishComparing a Kalman Filter and a Particle Filter in a Multiple Objects Tracking Application
| Title | Comparing a Kalman Filter and a Particle Filter in a Multiple Objects Tracking Application |
| Publication Type | Conference Paper |
| Año de publicación | 2007 |
| Autores | Marron, M, Garcia, JC, Sotelo, MA, Cabello-Aguilar, M, Pizarro, D, Huerta, F, Cerro, J |
| Idioma de publicación | English |
| Conference Name | 2007 IEEE International Symposium on Intelligent Signal Processing |
| Páginas | 1-6 |
| Editorial | IEEE |
| Conference Location | Alcalá de Henares, Spain |
| Fecha de publicación | 10/2007 |
| Numero ISBN | 978-1-4244-0829-0 |
| Palabras clave | Multi-Object Tracking, position estimation, Probabilistic Algorithms, robotics |
| DOI | 10.1109/WISP.2007.4447520 |
| URL | http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?asf_arn=null&asf_iid=null&asf_pun=4447489&asf_in=null&asf_rpp=null&asf_iv=null&asf_sp=null&asf_pn=3 |
| Abstract | Two of the most important solutions in position estimation are compared, in this paper, in order to test their efficiency in a multi-tracking application in an unstructured and complex environment. A Particle Filter is extended and adapted with a clustering process in order to track a variable number of objects. The other approach is to use a Kalman Filter with an association algorithm for each of the objects to track. Both algorithms are described in the paper and the results obtained with their real-time execution in the mentioned application are shown. Finally interesting conclusions extracted from this comparison are remarked at the end. |
| Resumen | Two of the most important solutions in position estimation are compared, in this paper, in order to test their efficiency in a multi-tracking application in an unstructured and complex environment. A Particle Filter is extended and adapted with a clustering process in order to track a variable number of objects. The other approach is to use a Kalman Filter with an association algorithm for each of the objects to track. Both algorithms are described in the paper and the results obtained with their real-time execution in the mentioned application are shown. Finally interesting conclusions extracted from this comparison are remarked at the end. |
| Attachment | Size |
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| wisp07_def.pdf | 337.98 KB |
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