Parking Slot Detection Algorithm Based on Keypoint Matching
Due to the diverse types of parking spaces,in more complex environments,the automatic parking system in-stalled on the smart vehicle may fail due to the inability to accurately detect the parking slot,resulting in a reduced driver's operating experience and an increased risk of accidents.This paper proposes a parking slot detection algorithm based on keypoint matching to address the problem of unclear parking space features caused by blurry parking lines,occlusion,and insufficient lighting.This paper uses keypoint heatmaps to detect the center and corner position coordinates of the entrance line;we utilize the affinity field of the unit direction vector to match the center point to the corresponding corner point.It represents the center direction of multiple regions as the edge direction of parking slots.This paper predicts the occupancy status of parking spaces by utilizing the occupancy of grid cells on the centerline.A self calibrated convolutional model YSCCNet based on YOLOv8 is designed for feature extraction,which can achieve parking slot detection with complete in-formation such as position,direction,and occupancy.
parking slot detectionkeypoint heatmapaffinity field matchingself-calibrated convolutional model