Fully Synthetic Pedestrian Anomaly Behavior Dataset Generation in Metaverse for Enhancing Autonomous Driving Object Detection

Fully Synthetic Pedestrian Anomaly Behavior Dataset Generation in Metaverse for Enhancing Autonomous Driving Object Detection

Pedestrian detection is fundamental in the realm of autonomous driving, relying on comprehensive datasets for accurate deep-learning methods. Detecting diverse pedestrian behaviors, including rare and near-accident cases, is necessary, however, there were limitations in the development of such speci...

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Bibliographic Details
Main Authors: Nang Htet Htet Aung, Paramin Sangwongngam, Rungroj Jintamethasawat, Lunchakorn Wuttisittikulkij
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Autonomous vehicles (AVs)
deep learning
pedestrian detection
pedestrian anomaly behaviors
synthetic dataset
metaverse
Online Access:https://ieeexplore.ieee.org/document/10749804/

Internet

https://ieeexplore.ieee.org/document/10749804/

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