Improved Parking Space Recognition via Grassmannian Deep Stacking Network with Illumination Correction

2021 ◽  
pp. 150-159
Author(s):  
Tee Connie ◽  
Michael Kah Ong Goh ◽  
Voon Chet Koo ◽  
Ken T. Murata ◽  
Somnuk Phon-Amnuaisuk
Keyword(s):  
Parking Space ◽  
Space Recognition

Suitable Parking Space Recognition for Autonomous Valet Parking

ETRI Journal ◽  
2015 ◽  
Author(s):  
Seung-Jun Han ◽  
Jeongdan Choi
Keyword(s):  
Parking Space ◽  
Space Recognition

scholarly journals Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

ETRI Journal ◽  
2015 ◽  
Vol 37 (6) ◽  
pp. 1220-1230 ◽  
Author(s):  
Seung-Jun Han ◽  
Jeongdan Choi
Keyword(s):  
Parking Space ◽  
Probability Maps ◽  
Space Recognition

scholarly journals Parking Space Recognition Method Based on Parking Space Feature Construction in the Scene of Autonomous Valet Parking

2021 ◽  
Vol 11 (6) ◽  
pp. 2759
Author(s):  
Shidian Ma ◽  
Weifeng Fang ◽  
Haobin Jiang ◽  
Mu Han ◽  
Chenxu Li
Keyword(s):  
Template Matching ◽  
Recognition Algorithm ◽  
Feature Construction ◽  
Parking Space ◽  
Light Conditions ◽  
Recognition Method ◽  
Matching Algorithm ◽  
Information Interaction ◽  
Similarity Calculation ◽  
Space Recognition

At present, the realization of autonomous valet parking (AVP) technology does not achieve information interaction between the parking spaces and vehicles, and accurate parking spaces information perception cannot be obtained when the accuracy of the search is not precise. In addition, when using the camera vision to identify the parking spaces, traditional parking space features such as parking lines and parking angles recognition are susceptible to light and environment. Especially when the vehicle nearby partially occupies the parking space to be parked, it is not easy to determine whether it is a valid empty parking space. This paper proposes a parking space recognition method based on parking space features in the scene of AVP. By constructing the multi-dimensional features containing the parking space information, the cameras are used to extract features’ contour, locate features’ position and recognize features. In this paper, a new similarity calculation formula is proposed to recognize the stained features through template matching algorithm. According to the relative position relationship between the feature and parking space, the identification of effective empty parking spaces and their boundaries is realized. The experimental results show that compared with the recognition of traditional parking lines and parking angles, this method can identify effective empty parking spaces even when the light conditions are complex and the parking spaces are partially occupied by adjacent vehicles, which simplifies the recognition algorithm and improves the reliability of the parking spaces identification.

scholarly journals Parking Space Recognition Based on Deep Convolutional Neural Network

2021 ◽  
Author(s):  
Zhuowen Chen ◽  
Zijun Gao ◽  
Jiaqi Li ◽  
Junjie Zhang ◽  
Yanan Dai ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Parking Space ◽  
Space Recognition

An improved parking space recognition algorithm based on panoramic vision

2021 ◽  
Author(s):  
Jindong Zhang ◽  
Tong Liu ◽  
Xuelong Yin ◽  
Xue Wang ◽  
Kunpeng Zhang ◽  
...  
Keyword(s):  
Recognition Algorithm ◽  
Parking Space ◽  
Panoramic Vision ◽  
Space Recognition

scholarly journals Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2261
Author(s):  
Changhao Piao ◽  
Jun Zhang ◽  
KyungHi Chang ◽  
Yan Li ◽  
Mingjie Liu
Keyword(s):  
System Performance ◽  
Trajectory Generation ◽  
Parking Space ◽  
Initial State ◽  
Recognition Error ◽  
Parking System ◽  
Automatic Parking ◽  
Sensor Information ◽  
Space Recognition ◽  
Real Vehicle

The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to parking space recognition error and trajectory generation for vehicle nonparallel initial state with parking space. In this study, the authors propose multi-sensor information ensemble for parking space recognition and adaptive trajectory generation method, which is also robust to vehicle nonparallel initial state. Both simulation and real vehicle experiments are conducted to prove that the proposed method can improve the automatic parking system performance.

Short–Term Prediction of Available Parking Space Based on Improved Wavelet Neural Network

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Jinfen Wang ◽  
Xiaofei Ye ◽  
Zhen Yang ◽  
Qiming Ye ◽  
Chang Yang
Keyword(s):  
Neural Network ◽  
Wavelet Neural Network ◽  
Parking Space ◽  
Short Term ◽  
Term Prediction ◽  
Short Term Prediction

Study on Parking Space Index of Typical Buildings in Weihai

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Peiyu Jiang ◽  
Xu Wang ◽  
Zhangyu Han
Keyword(s):  
Parking Space

Searching for a Parking Space

2005 ◽  
Vol 41 (2) ◽  
pp. 101-115 ◽  
Author(s):  
Eric Laurier
Keyword(s):  
Parking Space
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