%0 Book
%T Efficient human situation recognition using Sequential Monte Carlo in discrete state spaces
%A Nyolt, Martin
%D 2019
%C Rostock
%C Universität Rostock
%G English
%F 1678192589
%O vorgelegt von Martin Nyolt
%O GutachterInnen: Thomas Rudolf Kirste (Institute for Visual and Analytic Computing) ; Adelinde Maria Uhrmacher (Institute for Visual and Analytic Computing) ; Jesse Hoey (School of Computer Science)
%O Dissertation Universität Rostock 2019
%X This dissertation analyses these challenges and provides solutions for SMC methods. The large, categorical and causal state-space is the largest factor for the inefficiency of current SMC methods. The marginal filter is analysed in detail for its advantages in categorical states over the particle filter. An optimal pruning strategy for the marginal filter is derived that limits the number of samples.<eng>
%L 004
%9 theses
%9 Text
%9 Hochschulschrift
%R 10.18453/rosdok_id00002533
%U http://purl.uni-rostock.de/rosdok/id00002533
%U https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00002533-3
%U https://d-nb.info/1293657670/34
%U https://doi.org/10.18453/rosdok_id00002533