TY - CONF T1 - Comparing a Kalman Filter and a Particle Filter in a Multiple Objects Tracking Application T2 - 2007 IEEE International Symposium on Intelligent Signal Processing Y1 - 2007 A1 - Marta Marron A1 - Garcia, Juan Carlos A1 - Miguel Angel Sotelo A1 - M. Cabello A1 - Daniel Pizarro A1 - Francisco Huerta A1 - Jesus Cerro KW - Multi-Object Tracking KW - position estimation KW - Probabilistic Algorithms KW - robotics AB - 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. JF - 2007 IEEE International Symposium on Intelligent Signal Processing PB - IEEE CY - Alcalá de Henares, Spain SN - 978-1-4244-0829-0 UR - 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 ER -