Using Fast Classification of Static and Dynamic Environment for Improving Bayesian Occupancy Filter (BOF) and Tracking

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Source In IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV)
Author Baig, Qadeer, Perrollaz, Mathias, Botelho, Jander, Laugier, Christian
Maintainer CCSD
Last Updated June 4, 2026, 01:40 (UTC)
Created June 4, 2026, 01:40 (UTC)
Identifier hal-00757400
Language en
contributor Geometry and Probability for Motion and Action (E-MOTION) ; Centre Inria de l'Université Grenoble Alpes ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Grenoble (LIG) ; Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)
coverage Guangzou, China, China
creator Baig, Qadeer
date 2012-12-05T00:00:00
harvest_object_id 7ef8c126-770d-4e5f-a494-ddd8b530c209
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-09-27T00:00:00
set_spec type:COMM