Abstract
Pedestrian detection has never been an easy task for computer vision and the automotive industry. Systems like the advanced driver-assistance system (ADAS) highly rely on far-infrared (FIR) data captured to detect pedestrians at nighttime. The recent development of deep learning-based detectors has proven the excellent results of pedestrian detection in perfect weather conditions. However, it is still unknown what the performance in adverse weather conditions is. In this paper, we introduce a 16-bit thermal data dataset called ZUT (Zachodniopomorski Uniwersytet Technologiczny) as having the widest variety of fine-grained annotated images captured in the four biggest European Union countries captured during severe weather conditions. We also provide a synchronized Controller Area Network (CAN bus) data, including driving speed, brake pedal status, and outside temperature for future ADAS system development. Furthermore, we have tested and provided 16-bit depth modifications for the YOLOv3 deep neural network (DNN) based detector, reaching a mean Average Precision (mAP) up to 89.1%. The ZUT dataset is published and publicly available at IEEE Dataport and Github.
Highlights
The World Health Organization (WHO) each year announces the statistics of people injured in traffic accidents
The rest of the article is organized as follows: we provide an overview of the dataset, the methodology of how the dataset was collected, the description of annotations available, details of modifications done to Darknet deep neural network (DNN) implementation to support 16bit depth images, YOLOv3 and Tiny YOLOv3 (TINYv3) configuration changes, and the results of dataset evaluation
Law limitations were based on the selection criteria and General Data Protection Regulation (GDPR) rules, typical weather conditions based on season, car accident statistics, and traffic infrastructure
Summary
The World Health Organization (WHO) each year announces the statistics of people injured in traffic accidents. Even though the European Union has the safest roads in the world, there are more than 25 000 [4] people who lose their lives every year, and many more are seriously injured. Fog, snow, and wind are factors affecting visibility and act via a psycho-physiological function of the driver [5], [6], increasing the traffic accident rate by up to 13% [7], [8]. The EU introduces new safety measures in cars, lorries, and buses for advanced driver assistance systems (ADAS). The new systems support a new feature like intelligent speed assistance, advanced emergency braking and lane-keeping systems, frontal protection systems, driver drowsiness, attention
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
