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

Qadeer Baig 1 Mathias Perrollaz 1 Jander Botelho 1 Christian Laugier 1
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
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Conference papers
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Submitted on : Monday, November 26, 2012 - 5:36:51 PM
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Qadeer Baig, Mathias Perrollaz, Jander Botelho, Christian Laugier. Using Fast Classification of Static and Dynamic Environment for Improving Bayesian Occupancy Filter (BOF) and Tracking. In IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV), Dec 2012, Guangzou, China, China. ⟨hal-00757400⟩

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