Show Reference: "Person tracking based on a hybrid neural probabilistic model"

Person tracking based on a hybrid neural probabilistic model In Proceedings of the 21st international conference on Artificial neural networks - Volume Part II (2011), pp. 365-372 by Wenjie Yan, Cornelius Weber, Stefan Wermter
@inproceedings{yan-et-al-2011b,
    abstract = {This article presents a novel approach for a real-time person tracking system based on particle filters that use different visual streams. Due to the difficulty of detecting a person from a top view, a new architecture is presented that integrates different vision streams by means of a {Sigma-Pi} network. A short-term memory mechanism enhances the tracking robustness. Experimental results show that robust real-time person tracking can be achieved.},
    address = {Berlin, Heidelberg},
    author = {Yan, Wenjie and Weber, Cornelius and Wermter, Stefan},
    booktitle = {Proceedings of the 21st international conference on Artificial neural networks - Volume Part II},
    isbn = {978-3-642-21737-1},
    keywords = {ann, architecture, computational, cue-combination, hybrid, localization, model, particle-filter, probability, sigma-pi, unsupervised-learning, visual, visual-processing},
    location = {Espoo, Finland},
    pages = {365--372},
    posted-at = {2012-10-11 13:16:04},
    priority = {2},
    publisher = {Springer-Verlag},
    series = {ICANN'11},
    title = {Person tracking based on a hybrid neural probabilistic model},
    url = {http://portal.acm.org/citation.cfm?id=2029651},
    year = {2011}
}

See the CiteULike entry for more info, PDF links, BibTex etc.