Intelligent automobile single-target tracking method based on twin network

A smart car and twin network technology, applied in biological neural network models, neural learning methods, instruments, etc., can solve the problem of low precision of filtering tracking methods

Pending Publication Date: 2020-10-09
JIANGSU UNIV
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Among them, the filter class became the mainstream because of its simple structure, but with the deepening of researc

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
  • Intelligent automobile single-target tracking method based on twin network
  • Intelligent automobile single-target tracking method based on twin network
  • Intelligent automobile single-target tracking method based on twin network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0078] The present invention will be further described below in conjunction with accompanying drawing.

[0079] Such as figure 1 The overall operation flow of the algorithm of the present invention is shown. After the template and the image to be detected are extracted through the twin network composed of the Mish-channel-dark network, their corresponding feature information is obtained. Then the feature information is input into the similarity judgment branch and the quality evaluation branch, and finally the similarity is determined by cross-correlation calculation, and the template update is completed.

[0080] The concrete implementation process of the present invention comprises as follows:

[0081] Step1: Design mish convolution module (mish-convolutional)

[0082] Such as figure 2 As shown, the mish convolutional module (mish-convolutional) consists of a convolutional layer (conv2d), a batch normalization (BN) layer, and a sequence of mish activation layers.

[008...

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 discloses an intelligent automobile single-target tracking method based on a twin network. After a template and an image to be detected are extracted through a twin network formed by a Mish-channel-dark network to obtain feature information corresponding to the template and the image to be detected, then the feature information is input into a similarity judgment branch and a qualityevaluation branch, finally, the similarity is determined through cross-correlation calculation, and template updating is completed. The Mish-channel-park network is composed of a mish convolution module, an m-Residual module, a channel attention module and a structural body. According to the method, the reasoning capability and the anti-interference capability of the tracking algorithm are improved, the channel attention module is added, the tracking precision of the network is remarkably improved, the time for retrieving the object when the target disappears and reappears is shortened, and the practicability of the network is effectively improved. The twin network designed by the invention has better performance, and can achieve higher speed only by lower configuration during deployment.

Description

technical field [0001] The invention belongs to the technical field of intelligent vehicle vision, and in particular relates to a single-target tracking method for intelligent vehicles based on a twin network. Background technique [0002] Object tracking technology refers to the use of the size and position of the target in the initial frame of a given video sequence to determine the size and position of the target in subsequent frames. Through the target tracking technology, the computer can make full use of the acquired data information. Different from object detection, object tracking not only needs to obtain the current position information and classification information of the target, but also needs to analyze whether the current object is the previously determined object according to the relevant algorithm, which also makes this task have an extraordinary research value. Target tracking can be applied to unmanned driving, analyzing the movement of vehicles or pedest...

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): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V20/49G06V2201/07G06N3/047G06N3/045
Inventor 陈龙朱程铮蔡英凤王海李祎承孙晓强陈晓波
Owner JIANGSU UNIV
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap