Car Detection Based Algorithm For Automatic Parking Space Detection

Patel, Raj; Meduri, Praveen

doi:10.1109/icmla51294.2020.00220

Cited by 10 publications

(7 citation statements)

References 8 publications

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“…The method didn't require training procedure. Similar approach was also proposed by Patel and Meduri [15]. However, they adopted deep-learning architectures to identify the vehicle, and then track the vehicle.…”

Section: Literature Reviewmentioning

confidence: 97%

Detection of Empty/Occupied States of Parking Slots in Multicamera system using Mask R-CNN Classifier

Nugroho

Adi

Afandi³

2023

IJATR

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A fast growth of vehicles in big cities has an impact of arising road loads and difficulty of finding empty parking spaces. One solution to cope with the problem is to develop a parking management system which can provide useful information of available parking spaces to the potential users. This paper discusses about a new multicamera arrangement and the function to evaluate the empty/occupied states of the parking slots, as an alternative solution to the existing single camera system, The system adopted Mask R-CNN for its classifier, because of its capability to provide the polygon outputs for its detected objects, compared with the existing bounding box outputs provided by other classifiers. The proposed function has optimized the available information from all cameras, by considering the relative position of each camera to the parking spaces, and also capable of overcoming occlusion problem occurs in some cameras, The experiment shows that the capability of overcoming the occlusion problem has been validated, and its performance to evaluate the empty/occupied states of the parking slots was better than the single camera system to a certain threshold.

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Section: Literature Reviewmentioning

confidence: 97%

Detection of Empty/Occupied States of Parking Slots in Multicamera system using Mask R-CNN Classifier

Nugroho

Adi

Afandi³

2023

IJATR

View full text Add to dashboard Cite

show abstract

“…In [2] a car detection-based algorithm for automatic parking space detection aims to automate mapping by emphasizing car detection and available space identification. It indicates potential for a 90% reduction in human effort and nearly 100% detection when all spots are occupied.…”

Section: Literature Surveymentioning

confidence: 99%

Car Parking Slot Detection Using Yolo Algorithm

2024

IJSREM

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Finding free slots in the parking area has become a major problem that the modern society is facing nowadays, which also leads to traffic overcrowding at the parking area. As the number of vehicles are increasing at a quick pace find parking slots has become difficult. The proposed paper helps to solve the parking problem. In traditional parking system a person has to find vacant slot or a gate keeper needs to inform about the available parking slot at parking area. To address the issue, a system where the user will be able to know the number of vacant slots in a particular parking area along with total number of slots at the entrance of the parking area. As a critical component of this project, by built a car parking slot detection system which collects data from a camera at parking area. Today's most popular object detection model YOLO, is trained to achieve desired results with good precision scores at real-time speed. The model will be getting all the parking slots that are present in the parking area, to which marking boxes are drawn around for training. Real time processing is performed on the obtained data by the model to find whether the slot is vacant or occupied. Thus, it gives the information of available vacant slots to park the car at parking area. Key Words: YOLO, Object detection, Computer vision, Machine learning.

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“…user must specify the corners of the parking area and the number of slots, as well as camera homography matrix has to be estimated. Recently, two step automatic parking slot detection is proposed in Patel & Meduri (2020). At first, vehicle detection is performed using Faster R-CNN or Yolov4 and then vehicle tracking is performed to distinguish between stationary vehicles and moving vehicles.…”

Section: Related Workmentioning

confidence: 99%