scholarly journals A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

Sensors ◽  
2016 ◽  
Vol 16 (8) ◽  
pp. 1325 ◽  
Author(s):  
Yongzheng Xu ◽  
Guizhen Yu ◽  
Yunpeng Wang ◽  
Xinkai Wu ◽  
Yalong Ma
Keyword(s):  
Detection Method ◽  
Vehicle Detection ◽  
Hybrid Vehicle ◽  
Uav Images

Improved Real-Time Vehicle Detection Method Based on YOLOV3

2020 ◽  
Vol 57 (10) ◽  
pp. 101507
Author(s):  
李汉冰 Li Hanbing ◽  
徐春阳 Xu Chunyang ◽  
胡超超 Hu Chaochao
Keyword(s):  
Real Time ◽  
Detection Method ◽  
Vehicle Detection

scholarly journals An Improved Roadside Parking Space Occupancy Detection Method Based on Magnetic Sensors and Wireless Signal Strength

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2348 ◽  
Author(s):  
Liangliang Lou ◽  
Jinyi Zhang ◽  
Yong Xiong ◽  
Yanliang Jin
Keyword(s):  
Detection Method ◽  
Dead Zone ◽  
Sampling Rate ◽  
Vehicle Detection ◽  
Magnetic Sensors ◽  
Experimental Results ◽  
Detection Accuracy ◽  
Parking Space ◽  
Wireless Transceivers ◽  
Occupancy Detection

Smart Parking Management Systems (SPMSs) have become a research hotspot in recent years. Many researchers are focused on vehicle detection technology for SPMS which is based on magnetic sensors. Magnetism-based wireless vehicle detectors (WVDs) integrate low-power wireless communication technology, which improves the convenience of construction and maintenance. However, the magnetic signals are not only susceptible to the adjacent vehicles, but also affected by the magnetic signal dead zone of high-chassis vehicles, resulting in a decrease in vehicle detection accuracy. In order to improve the vehicle detection accuracy of the magnetism-based WVDs, the paper introduces an RF-based vehicle detection method based on the characteristics analysis of received signal strengths (RSSs) generated by the wireless transceivers. Since wireless transceivers consume more energy than magnetic sensors, the proposed RF-based method is only activated to extract the data characteristics of RSSs to further judge the states of vehicles when the data feature of magnetic signals is not sufficient to provide accurate judgment on parking space status. The proposed method was evaluated in an actual roadside parking lot and experimental results show that when the sampling rate of magnetic sensor is 1 Hz, the vehicle detection accuracy is up to 99.62%. Moreover, compared with machine-learning-based vehicle detection method, the experimental results show that our method has achieved a good compromise between detection accuracy and power consumption.

Video Vehicle Detection Method Based on Multiple Color Space Information Fusion

2012 ◽  
Vol 546-547 ◽  
pp. 721-726
Author(s):  
Hong Xiang Shao ◽  
Xiao Ming Duan
Keyword(s):  
Information Fusion ◽  
Traditional Method ◽  
Detection Method ◽  
Color Space ◽  
Vehicle Detection ◽  
Data Accuracy ◽  
Traffic Information ◽  
Detection Accuracy ◽  
Relative Independence ◽  
Hsi Color Space

A detection method which selective fuses the nine detection results of RGB, YCbCr and HSI color space according to the image color space relative independence of each component and complementarities is approached in order to improve vehicle video detection accuracy. The method fuses three different detection results in nine components by the value of H when the value of both S and I are higher and does another three detection results when the value of both S and I are smaller. Experiments show that the method compared to the traditional method using only the detection results of the brightness component improved substantial, reduced empty of the detected vehicle a large extent and increased traffic information data accuracy depending on the detection result.

scholarly journals A Novel Vehicle Detection Method Based on the Fusion of Radio Received Signal Strength and Geomagnetism

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 58 ◽  
Author(s):  
Liangliang Lou ◽  
Jinyi Zhang ◽  
Yong Xiong ◽  
Yanliang Jin
Keyword(s):  
Error Detection ◽  
Detection Method ◽  
Signal Strength ◽  
Vehicle Detection ◽  
Received Signal Strength ◽  
Detection Accuracy ◽  
Detection Problem ◽  
Traffic Light ◽  
Radio Stations ◽  
Multiple Detection

A geomagnetic signal blind zone exists between the front and rear axle of high-chassis vehicle such as trucks and buses, which leads to multiple-detection problem in detecting those vehicles running at low speed on roads or error-detection problem in the case of the stopping position of the vehicle is not standard when waiting for the traffic light to change. In order to improve the detection accuracy of any type of vehicle running at any speed, a novel two-sensors data fusion vehicle detection method through combining received signal strength from radio stations with geomagnetism around vehicles is designed and verified in the paper. Experimental results show that the accuracy of our proposed method can reach 95.4% and traditional single magnetism-based detection method was only 83.4% in the detection of high-chassis vehicles.

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