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
Document type :
Conference papers
Complete list of metadatas
https://hal.inria.fr/hal-00757400
Contributor : Qadeer Baig <>
Submitted on : Monday, November 26, 2012 - 5:36:51 PM
Last modification on : Friday, October 25, 2019 - 1:21:37 AM

Identifiers

  • HAL Id : hal-00757400, version 1

Collections

CNRS | INRIA | UGA | LIG | LIG_SIC_E-MOTION

Citation

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⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

361

 

 

Contact

archive-ouverte@inria.fr