Target Tracking Method Based on Multiple Siamese Neural Networks and Regional Neural Networks

A neural network and target tracking technology, applied in biological neural network models, neural learning methods, image analysis, etc., to achieve the effect of real-time target tracking

Active Publication Date: 2021-06-18
XIAMEN UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a method that can convert the target tracking problem into an updateable instance retrieval problem by using a pre-trained multiple twin neural network, and at the same time adopt a pre-trained regional neural network to solve the re-detection problem after the target is lost Target Tracking Method Based on Multiple Siamese Neural Networks and Regional Neural Networks

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
  • Target Tracking Method Based on Multiple Siamese Neural Networks and Regional Neural Networks
  • Target Tracking Method Based on Multiple Siamese Neural Networks and Regional Neural Networks
  • Target Tracking Method Based on Multiple Siamese Neural Networks and Regional Neural Networks

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] The method of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0043] see figure 1 , the implementation of the embodiment of the present invention includes the following steps:

[0044] 1) Given a video sequence in which the first frame contains a marked target, define the size C of the original input image frame f (in represents a rectangular area), the original size of the target C o , and the search range C of the target s . where the target's original size C o , and the search range C of the target s It will be used as the input of the multiple siamese neural network for object tracking based on instance retrieval. The size C of the original input image frame f , will be used as input to the regional neural network for re-detection to achieve missing objects.

[0045] 2) Based on the size C of the image frame defined in step 1) f , the original size of the target C o , and the search...

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

A target tracking method based on multiple twin neural networks and regional neural networks, involving computer vision technology. Transform the object tracking problem into an updatable instance retrieval problem by using a pretrained multi-Siamese neural network. At the same time, a pre-trained regional neural network is used to solve the problem of re-detection after the target is lost. First, multiple twin neural networks are trained on a large visual recognition database to retrieve target instances, and then the pre-trained regional neural network is used to re-detect lost targets during the target tracking process, further assisting in obtaining the final target position and realizing real-time targets track. First, multiple twin neural networks are trained on a large visual recognition database to retrieve target instances, and then the pre-trained regional neural network is used to re-detect lost targets during the target tracking process, further assisting in obtaining the final target position and realizing real-time targets tracked.

Description

technical field [0001] The invention relates to computer vision technology, in particular to a target tracking method based on multiple twin neural networks and regional neural networks. Background technique [0002] An important source of human perception of the world is through image information. Studies have shown that about 80% to 90% of the information that humans obtain from the outside world comes from image information obtained by human eyes. Object tracking is a common vision task in image information understanding. Target tracking has a wealth of applications in real life, such as real-time tracking of the target of interest in the video sequence provided by the user; conference or venue managers can use the automated target tracking system to analyze the action patterns of the venue personnel to Make better decisions. Therefore, it is of great practical significance to use computer vision to realize automatic target tracking. [0003] Object tracking is one of ...

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
Patent Type & AuthorityPatents(China)
IPC IPC(8): G06T7/246G06N3/08
CPCG06N3/08G06T2207/10016G06T7/246
Inventor王菡子刘祎严严
OwnerXIAMEN UNIV