Construction of computer visual dataset for autonomous driving in sand‐dust weather

Abstract

AbstractWith the wide application of vision‐based autonomous driving and mobile robots, the impact of frequent sand‐dust weather on computer vision applications in landlocked countries during spring and autumn has also attracted more and more attention. Although there has been a lot of research on sand‐dust image enhancement, no research has been conducted on how to improve the positioning accuracy of vision‐based autonomous driving or mobile robots in sand‐dust environments, especially because there is currently a lack of dataset to evaluate visual positioning in sand‐dust weather. Therefore, a complete set of visual positioning dataset construction methods in sand‐dust weather is proposed to fill the gap in the evaluation dataset of application fields such as autonomous driving or mobile robot attitude estimation in sand‐dust weather. At the same time, this method is also suitable for the construction of visual positioning dataset under haze and other similar weather. In addition, this paper further demonstrates to readers how to use the converted dust visual positioning dataset to conduct positioning evaluation experiment of automatic driving in sand‐dust weather.