Parking Space Detection
Parking Space Detection
Datasets
Parking Space Detection
File
Parking Detection
Use Case
Parking Detection
Description
Explore our Top-View Parking Detection Dataset, crafted for precise PSV view construction. Featuring high-quality imagery and manual annotations.
About the Dataset
To achieve precise detection of parking spaces using computer vision (CV) methods for constructing PSV (Parking Space View) perspectives, we developed this dataset by refining two open-source datasets: Aerial View Car Detection for YOLOv5 and the Parking Space Detection & Classification Dataset. We filtered and retained images specifically useful for parking space detection and manually labeled the standard detection frames for each parking space.
This effort has culminated in a manuscript submitted to the IEEE Transactions on Intelligent Transportation Systems, which is currently under review. If this dataset proves beneficial for your research or work, we encourage you to follow our updates. Should our manuscript be accepted for publication, we kindly request that you cite our paper, as this recognition will greatly encourage us to continue providing valuable datasets for the research community and open source projects.
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Top-View Imagery: High-quality top-view images specifically curated for parking space detection.
Manual Annotations: Each parking space in the images is manually labeled to ensure accurate detection frames.
Filtered and Refined: Derived from open-source datasets, our dataset has been carefully filtered to focus on parking space detection, eliminating irrelevant data.
Versatility: Suitable for a range of applications, including autonomous vehicle parking systems, smart city infrastructure planning, and CV research.
Research and Development: Ideal for researchers and developers working on intelligent transportation systems, urban planning, and AI-driven parking solutions.
Potential Applications:
Autonomous Vehicles: Enhancing the parking capabilities of self-driving cars.
Smart Cities: Integrating with urban planning systems to optimize parking space utilization.
AI Research: Contributing to advancements in computer vision and intelligent transportation systems.
Commercial Solutions: Providing data for developing commercial parking assistance technologies.
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