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Communication Dans Un Congrès Année : 2023

Holistic Parking Slot Detection with Polygon-Shaped Representations

Lihao Wang
  • Fonction : Auteur
  • PersonId : 1355930
Antonyo Musabini
  • Fonction : Auteur
  • PersonId : 1355931
Christel Leonet
  • Fonction : Auteur
  • PersonId : 1355932
Rachid Benmokhtar
  • Fonction : Auteur
  • PersonId : 1240816
Amaury Breheret
Chaima Yedes
  • Fonction : Auteur
  • PersonId : 1355933
Fabian Bürger
  • Fonction : Auteur
  • PersonId : 1355934
Thomas Boulay
  • Fonction : Auteur
  • PersonId : 1355935
Xavier Perrotton
  • Fonction : Auteur
  • PersonId : 1355936

Résumé

Current parking slot detection in advanced driverassistance systems (ADAS) primarily relies on ultrasonic sensors. This method has several limitations such as the need to scan the entire parking slot before detecting it, the incapacity of detecting multiple slots in a row, and the difficulty of classifying them. Due to the complex visual environment, vehicles are equipped with surround view camera systems to detect vacant parking slots. Previous research works in this field mostly use image-domain models to solve the problem. These two-stage approaches separate the 2D detection and 3D pose estimation steps using camera calibration. In this paper, we propose onestep Holistic Parking Slot Network (HPS-Net), a tailor-made adaptation of the You Only Look Once (YOLO)v4 algorithm. This camera-based approach directly outputs the four vertex coordinates of the parking slot in topview domain, instead of a bounding box in raw camera images. Several visible points and shapes can be proposed from different angles. A novel regression loss function named polygon-corner Generalized Intersection over Union (GIoU) for polygon vertex position optimization is also proposed to manage the slot orientation and to distinguish the entrance line. Experiments show that HPS-Net can detect various vacant parking slots with a F1score of 0.92 on our internal Valeo Parking Slots Dataset (VPSD) and 0.99 on the public dataset PS2.0. It provides a satisfying generalization and robustness in various parking scenarios, such as indoor (F1: 0.86) or paved ground (F1: 0.91). Moreover, it achieves a real-time detection speed of 17 FPS on Nvidia Drive AGX Xavier. A demo video can be found at https://streamable.com/75j7sj.

Dates et versions

hal-04473457 , version 1 (27-02-2024)

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Citer

Lihao Wang, Antonyo Musabini, Christel Leonet, Rachid Benmokhtar, Amaury Breheret, et al.. Holistic Parking Slot Detection with Polygon-Shaped Representations. International Conference on Intelligent Robots and Systems (IROS), IEEE/RSJ, Oct 2023, Detroit, United States. ⟨10.1109/iros55552.2023.10342486⟩. ⟨hal-04473457⟩
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