Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Détection d'obstacles par vision et LiDAR par temps de brouillard pour les véhicules autonomes

Abstract : This work concerns the generation of a synthetic fog dataset based on available datasets in good weather conditions. A synthetic dataset is necessary because it is not always possible to collect real data under degraded conditions. In addition, post-processing such as labeling or filtering data is not easy and time-consuming. A 3D object detection algorithm for autonomous vehicles is then implemented and evaluated on the dataset produced in order to analyze the impact of the weather on its performance. In the light of the results obtained, perspectives are proposed to improve performance of the proposed method earlier.
Document type :
Preprints, Working Papers, ...
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-03241464
Contributor : Nguyen Anh Minh Mai <>
Submitted on : Friday, May 28, 2021 - 4:25:44 PM
Last modification on : Wednesday, June 9, 2021 - 10:00:34 AM

File

Minh_ORASIS_2021.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03241464, version 1

Citation

Nguyen Anh Minh Mai, Pierre Duthon, Louahdi Khoudour, Alain Crouzil, Sergio A. Velastin. Détection d'obstacles par vision et LiDAR par temps de brouillard pour les véhicules autonomes. 2021. ⟨hal-03241464⟩

Share

Metrics

Record views

116

Files downloads

66