Vehicle target detection method, system and device based on YOLOv2

A target detection and vehicle technology, applied in the field of detection and vehicle identification, can solve the problems of low target detection accuracy, poor detection effect of small targets, and difficulty in extracting small images.

Inactive Publication Date: 2019-11-12
NANJING UNIV OF TECH
View PDF2 Cites 38 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the detection effect of the YOLOv2 model on small targets is relatively poor, mainly because the image becomes smaller after the operation of the convolution layer and the pooling layer, and th...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Vehicle target detection method, system and device based on YOLOv2
  • Vehicle target detection method, system and device based on YOLOv2
  • Vehicle target detection method, system and device based on YOLOv2

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0081] The application of this method will be described in detail below with reference to the accompanying drawings.

[0082] The present invention solves the existing technical problems through the following technical solutions:

[0083] Such as figure 1 As shown, the present invention discloses a vehicle target detection method based on YOLOv2 network, comprising the following steps:

[0084] Step 1, collect pattern data and process to obtain a sample data set; this experimental data set is extracted from the video taken by the car driving recorder, which contains a large number of vehicle targets; the sample data set is divided into training data set and test data set , a total of 8,000 training set pictures, including more than 35,000 vehicle targets; 2,000 test set pictures, including more than 9,900 vehicle targets;

[0085] Step 2, build the network structure of the improved YOLOv2 model based on the YOLOv2 model, realize multi-scale input, and change the output size...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a vehicle target detection method based on YOLOv2. The method comprises the steps of collecting pattern data and processing the pattern data to obtain a sample data set; constructing an improved YOLOv2 model, and improving the network structure of the YOLOv2 basic model; designing a loss function by adopting a comparison normalization thought; performing model training, wherein the training process of the whole network is divided into classification network training and detection network training; and model verification: verifying the model obtained by training by usingthe verification data set, and testing the recognition capability of the model. And the algorithm is subjected to experimental comparison with a recently popular algorithm to verify the effectivenessof the algorithm. The improved YOLOv2 model established by the invention can improve the recognition rate of small-scale vehicle targets. Under various complex conditions, most of target vehicles canbe detected, and the recognition speed and precision are higher than those of other conventional algorithms.

Description

technical field [0001] The invention relates to a vehicle target detection method, system and equipment, in particular to a method for identifying and detecting vehicles in complex traffic scenes. Background technique [0002] In recent years, with the growth of market demand and the continuous development of artificial intelligence, autonomous driving has gradually become one of the hot issues studied by various scholars. As an important step in automatic driving, vehicle target detection is also one of the main research issues. In intelligent traffic monitoring video, target detection technology has also been widely used, such as the detection and positioning of vehicles and pedestrians, and the automatic toll collection system of toll stations. At present, in the unmanned driving that has been applied, the target detection technology is also fully utilized. The system uses video and images as the research object, and uses target detection technology to detect and judge w...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/584G06N3/045G06F18/23213G06F18/214
Inventor 刘帅易辉史家鹏张杰
Owner NANJING UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products