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 language | English |
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Title of host publication | The 34th British Machine Vision Conference |
Publisher | The British Machine Vision Association |
Number of pages | 12 |
Publication status | Published - 2023 |
Event | 34th British Machine Vision Conference: BMVC 2023 - Aberdeen, United Kingdom Duration: 20 Nov 2023 → 24 Nov 2023 |
Conference
Conference | 34th British Machine Vision Conference |
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Country/Territory | United Kingdom |
City | Aberdeen |
Period | 20/11/23 → 24/11/23 |