LaneAF: Robust Multi-Lane Detection With Affinity Fields

• Published in: IEEE robotics and automation letters Vol. 6; no. 4; pp. 7477 - 7484
• Main Authors: Abualsaud, Hala, Liu, Sean, Lu, David B., Situ, Kenny, Rangesh, Akshay, Trivedi, Mohan M.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Affinity; Clustering; Computer architecture; Datasets; Deep learning; deep learning for visual perception; Error correction; Feature extraction; Lane detection; Masks; Object detection; Pixels; Post-production processing; Qualitative analysis; Roads; Segmentation; segmentation and categorization; Semantics; Task analysis

This study presents an approach to lane detection involving the prediction of binary segmentation masks and per-pixel affinity fields. These affinity fields, along with the binary masks, can then be used to cluster lane pixels horizontally and vertically into corresponding lane instances in a post-p...