YOLOv3-based multi-lane traffic flow counting and vehicle tracking method

A vehicle tracking and traffic flow technology, applied in the field of traffic big data, can solve the problems of insufficient accuracy and vehicle classification, and achieve the effect of improving speed and accuracy

Inactive Publication Date: 2019-06-07
HUAIYIN INSTITUTE OF TECHNOLOGY
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For detection methods using video, there are many traditional detection methods using

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[0026] The present invention will be further described below in conjunction with the drawings and specific embodiments.

[0027] Such as figure 1 As shown, the embodiment of the present invention discloses a YOLOv3-based multi-lane traffic counting and expressway vehicle tracking method, including the following steps:

[0028] 1. Extract features from the input image through the feature extraction network.

[0029] Yolo's Convolutional Neural Network (CNN) divides the input image into S x S grids, such as figure 2 As shown, then each cell is responsible for detecting the targets whose center point falls within the grid, and each cell will predict B bounding boxes and the confidence score of the bounding box. The so-called confidence includes two aspects, one is the probability that the bounding box contains the target, and the other is the accuracy of the bounding box. The former is denoted as Pr(object). When the bounding box is the background (that is, the target is not included)...

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Abstract

The invention discloses a YOLOv3-based multi-lane traffic flow counting and vehicle tracking method. According to the method, features of an inputted image are extracted by a feature extraction network and an image location and a category probability value are predicted; two adjacent frames of detected vehicle locations are compared and whether the center pointer of the frame of vehicle marking frame is located in a last frame of vehicle marking frame is determined to determine whether the vehicles are the same one, thereby realizing tracking; and with a set detection line, a traffic flow of each lane is obtained based on a line-frame position relationship. Therefore, tracking of the vehicle and vehicle counting at any lane can be realized; the detection speed and the accuracy are also greatly improved; and a traffic accident can be detected.

Description

technical field [0001] The present invention relates to the field of traffic big data, in particular to a multi-lane traffic flow counting and vehicle tracking method based on YOLOv3 (YOLOv3: An Incremental Improvement). Background technique [0002] Since modern times, with the rapid development of economy, the modernization process of transportation has been promoted. While enjoying the convenience brought by modern transportation, it has also brought huge pressure on urban roads. At present, the safety operation status of expressway in our country is not optimistic. Frequent traffic accidents and deteriorating traffic environment have caused huge losses to the country and people's life and property, and seriously damaged the basic service functions of highways. In order to improve the traffic capacity of the road, ensure the safety and smoothness of the road, timely and effectively rescue and deal with traffic accidents, reduce traffic delays caused by traffic accidents ...

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Application Information

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IPC IPC(8): G08G1/01G08G1/065G06K9/00G06N3/04
Inventor 高尚兵汪辉蔡创新周君黄子赫朱全银李翔曹苏群周建李文婷张莉雯谷文潭
Owner HUAIYIN INSTITUTE OF TECHNOLOGY
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