<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marta Marron</style></author><author><style face="normal" font="default" size="100%">Miguel Angel Sotelo</style></author><author><style face="normal" font="default" size="100%">Garcia, Juan Carlos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Combined Stochastic-Deterministic Solution for Tracking Multiple Objects with an Stereo-Vision System</style></title><secondary-title><style face="normal" font="default" size="100%">WSEAS Transactions on Signal Processing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">bayesian estimation</style></keyword><keyword><style  face="normal" font="default" size="100%">Multi-Object Tracking</style></keyword><keyword><style  face="normal" font="default" size="100%">multimodal probability distribution</style></keyword><keyword><style  face="normal" font="default" size="100%">Particle Filters</style></keyword><keyword><style  face="normal" font="default" size="100%">visual tracking</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2006</style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">https://mail.geintra-uah.org/en/system/files/private/journal3.pdf</style></url></related-urls></urls><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">253-260</style></pages><language><style face="normal" font="default" size="100%">English</style></language><abstract><style face="normal" font="default" size="100%">In this paper, the authors propose the use of a probabilistic algorithm to develop a multi-object tracking task. Different solutions have already been proposed by the scientific community to find a solution for this application, and the particle filter is proven to be the best choice in this case as the multimodality character of this Bayes filter implementation can be well-spent: an only particle filter can be used to track a variable number of objects. On the other hand, the flexibility of the particle filter can become in a lack of robustness for the estimator, so a deterministic algorithm is added to the standard filter to increase it. In the following paragraphs the global combined algorithm is described and different tests based on stereo-vision information are also included, proving the reliability of the proposal tracker</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record></records></xml>