Pedestrian tracking method based on twin neural network

A neural network and pedestrian tracking technology, which is applied in the field of pedestrian tracking based on twin neural networks, can solve the problems of large image noise, reduced search range, and no longer meeting the needs of pedestrian tracking.

Pending Publication Date: 2020-10-23
ZHEJIANG SCI-TECH UNIV
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

Due to the posture changes, size changes, appearance changes and pedestrian occlusions of pedestrian targets during motion, it is very difficult to achieve accurate tracking of pedestrians.
[0003] Early target tracking algorithms were mainly based on target modeling or tracking target features. The main methods are: (1) Feature matching method, first extracting target features, and then finding the most similar features in subsequent frames for target positio

Method used

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  • Pedestrian tracking method based on twin neural network
  • Pedestrian tracking method based on twin neural network
  • Pedestrian tracking method based on twin neural network

Examples

Experimental program
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Effect test

Embodiment 1

[0089] Embodiment 1, a kind of pedestrian tracking method based on twin neural network, such as figure 1 , including the following steps:

[0090] S01, video input

[0091] Input the video file containing the object to be tracked into the computer, each frame of video image included in the video file, and the video file is collected by the camera and other monitoring equipment outdoors or indoors;

[0092] S02. Pedestrian mark:

[0093] For each frame of video image input by S01, use DPM pedestrian detection technology to detect and mark the position of pedestrians on each frame of video image, and obtain a video sequence with pedestrian position marks;

[0094] The DPM pedestrian detection technology is a conventional technology, for example, refer to the DPM pedestrian detection algorithm published in "IEEE Transactions on Pattern Analysis & Machine Intelligence, 2010." by Felzenszwalb et al.

[0095] S03. Obtain the time-space group of pedestrians:

[0096] Split the vi...

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Abstract

The invention belongs to the field of computer vision, and particularly relates to a pedestrian tracking method based on a twin neural network, which comprises the following steps: inputting a video;performing pedestrian marking; acquiring a pedestrian space-time group; establishing and training a twin neural network, and storing the trained twin neural network; obtaining a pedestrian short track; and obtaining pedestrian long trajectories. By adopting the pedestrian tracking method to track pedestrians, the accuracy of pedestrian tracking is effectively improved.

Description

technical field [0001] The invention belongs to the field of computer vision, in particular to a pedestrian tracking method based on twin neural networks. Background technique [0002] With the development of artificial intelligence technology, computer vision has been widely used in human daily life such as smart home, video surveillance and intelligent transportation, and pedestrian tracking is one of the key issues in these fields. Due to the pose changes, size changes, appearance changes and pedestrian occlusions of pedestrian targets during motion, it is very difficult to achieve accurate tracking of pedestrians. [0003] Early target tracking algorithms were mainly based on target modeling or tracking target features. The main methods are: (1) Feature matching method, first extracting target features, and then finding the most similar features in subsequent frames for target positioning; (2) Based on the search method, people add the prediction algorithm to the tracki...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08G06T7/246
CPCG06N3/084G06T7/246G06T2207/10016G06T2207/20081G06T2207/20084G06T2207/30196G06T2207/30232G06T2207/30241G06V40/103G06N3/048G06N3/045G06F18/241
Inventor 王云涛潘海鹏马淼
Owner ZHEJIANG SCI-TECH UNIV
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