# Parking Spot Classification based on surround view camera system

arXiv: https://arxiv.org/abs/2310.12997 · HTML: https://mlsanity.com/paper/2310.12997/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 21 references that are in the map.
- First posted on arXiv 5 Oct 2023.

## Builds on (most cited first, 10 of 10)

- [You Only Look Once: Unified, Real-Time Object Detection](https://mlsanity.com/paper/1506.02640/) (2015)
- [SSD: Single Shot MultiBox Detector](https://mlsanity.com/paper/1512.02325/) (2015)
- [YOLOv3: An Incremental Improvement](https://mlsanity.com/paper/1804.02767/) (2018)
- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [YOLO9000: Better, Faster, Stronger](https://mlsanity.com/paper/1612.08242/) (2016)
- [AVP-SLAM: Semantic Visual Mapping and Localization for Autonomous Vehicles in the Parking Lot](https://mlsanity.com/paper/2007.01813/) (2020)
- [PSDet: Efficient and Universal Parking Slot Detection](https://mlsanity.com/paper/2005.05528/) (2020)
- [End-to-End Trainable One-Stage Parking Slot Detection Integrating Global and Local Information](https://mlsanity.com/paper/2003.02445/) (2020)
- [Surround-view Fisheye BEV-Perception for Valet Parking: Dataset, Baseline and Distortion-insensitive Multi-task Framework](https://mlsanity.com/paper/2212.04111/) (2022)
- [SPFCN: Select and Prune the Fully Convolutional Networks for Real-time Parking Slot Detection](https://mlsanity.com/paper/2003.11337/) (2020)

## Built on by (most cited first, 2 of 2)

- [Click-Calib: A Robust Extrinsic Calibration Method for Surround-View Systems](https://mlsanity.com/paper/2501.01557/) (2025)
- [DMV-AVP: Distributed Multi-Vehicle Autonomous Valet Parking Using Autoware](https://mlsanity.com/paper/2601.16327/) (2026)

## Abstract (arXiv)

Surround-view fisheye cameras are commonly used for near-field sensing in automated driving scenarios, including urban driving and auto valet parking. Four fisheye cameras, one on each side, are sufficient to cover 360deg around the vehicle capturing the entire near-field region. Based on surround view cameras, there has been much research on parking slot detection with main focus on the occupancy status in recent years, but little work on whether the free slot is compatible with the mission of the ego vehicle or not. For instance, some spots are handicap or electric vehicles accessible only. In this paper, we tackle parking spot classification based on the surround view camera system. We adapt the object detection neural network YOLOv4 with a novel polygon bounding box model that is well-suited for various shaped parking spaces, such as slanted parking slots. To the best of our knowledge, we present the first detailed study on parking spot detection and classification on fisheye cameras for auto valet parking scenarios. The results prove that our proposed classification approach is effective to distinguish between regular, electric vehicle, and handicap parking spots.