UrOAC: Urban objects in any-light conditions.

ABSTRACT: In the past years, several works on urban object detection from the point of view of a person have been made. These works are intended to provide an enhanced understanding of the environment for blind and visually challenged people. The mentioned approaches mostly rely in deep learning and machine learning methods. Nonetheless, these approaches only work with direct and bright light, namely, they will only perform correctly on daylight conditions. This is because deep learning algorithms require large amounts of data and the currently available datasets do not address this matter. In this work, we propose UrOAC, a dataset of urban objects captured in a range of different lightning conditions, from bright daylight to low and poor night-time lighting conditions. In the latter, the objects ar

SUBMITTER: Gomez-Donoso F 

PROVIDER: S-EPMC9058561 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature