A Dataset for Temporal Semantic Segmentation Dedicated to Smart Mobility of Wheelchairs on Sidewalks - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Imaging Année : 2022

A Dataset for Temporal Semantic Segmentation Dedicated to Smart Mobility of Wheelchairs on Sidewalks

Résumé

In smart mobility, the semantic segmentation of images is an important task for a good understanding of the environment. In recent years, many studies have been made on this subject, in the field of Autonomous Vehicles on roads. Some image datasets are available for learning semantic segmentation models, leading to very good performance. However, for other types of autonomous mobile systems like Electric Wheelchairs (EW) on sidewalks, there is no specific dataset. Our contribution presented in this article is twofold: (1) the proposal of a new dataset of short sequences of exterior images of street scenes taken from viewpoints located on sidewalks, in a 3D virtual environment (CARLA); (2) a convolutional neural network (CNN) adapted for temporal processing and including additional techniques to improve its accuracy. Our dataset includes a smaller subset, made of image pairs taken from the same places in the maps of the virtual environment, but from different viewpoints: one located on the road and the other located on the sidewalk. This additional set is aimed at showing the importance of the viewpoint in the result of semantic segmentation.

Dates et versions

hal-03751973 , version 1 (16-08-2022)

Identifiants

Citer

Benoit Decoux, Redouane Khemmar, Nicolas Ragot, Arthur Venon, Marcos Grassi-Pampuch, et al.. A Dataset for Temporal Semantic Segmentation Dedicated to Smart Mobility of Wheelchairs on Sidewalks. Journal of Imaging, 2022, 8 (8), pp.216. ⟨10.3390/jimaging8080216⟩. ⟨hal-03751973⟩
19 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More