A Comprehensive Crossroad Camera Dataset of Mobility Aid Users

Ludwig Mohr*, Nadezda Kirillova, Horst Possegger, Horst Bischof

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Improving the safety of traffic participants and reducing the severity of injuries as well as the number of fatalities in the event of accidents is becoming ever more important in the development of vehicles and transportation infrastructure. The most vulnerable group of road users is unquestionably pedestrians, of which people with mobility impairments are especially at risk due to reduced reaction speed or reduced visibility due to smaller silhouettes or unusual postures. Successful strategies for increasing safety by reducing the likelihood of accidents include architectural improvements in planning of pedestrian crossings, as well as advancements in their operation. These strategies can benefit from camera based pedestrian detection systems, yet pedestrians using mobility aids are highly underrepresented in common datasets for object detection and classification, if present at all. To fill this gap and enable researchers to develop methods considering pedestrians in their mobility, we present a novel dataset of pedestrians using mobility aids, together with evaluations of state-of-the-art methods for classification and detection.
Original languageEnglish
Title of host publicationThe 34th British Machine Vision Conference
PublisherThe British Machine Vision Association
Number of pages12
Publication statusPublished - 2023
Event34th British Machine Vision Conference: BMVC 2023 - Aberdeen, United Kingdom
Duration: 20 Nov 202324 Nov 2023

Conference

Conference34th British Machine Vision Conference
Country/TerritoryUnited Kingdom
CityAberdeen
Period20/11/2324/11/23

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