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Carried object detection and gait recognition method based on improved twin neural network

A neural network and gait recognition technology, applied in the field of image processing and computer vision research

Active Publication Date: 2020-02-07
HENAN UNIVERSITY
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Problems solved by technology

[0019] In order to solve the problem that the traditional twin neural network has a single input structure, it must be divided into two steps to solve the problem of carrying object state detection in the field of intelligent monitoring. The present invention provides a method for carrying object detection and gait recognition based on an improved twin neural network , which can simultaneously realize gait recognition and carrying status detection, saving time and effort

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  • Carried object detection and gait recognition method based on improved twin neural network
  • Carried object detection and gait recognition method based on improved twin neural network
  • Carried object detection and gait recognition method based on improved twin neural network

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Embodiment Construction

[0089] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0090] Such as figure 1 Shown: a kind of carrier detection and gait recognition method based on improved twin neural network of the present invention, it is characterized in that, comprises the following steps:

[0091] Step 1: Read the two videos before and after entering and exiting the sensitive place;

[0092] Specifically, the video before and after entering and exiting the sensitive place is collected by the camera, the former video is the video when entering the sensitive place, and the latter video is...

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Abstract

The invention provides a carried object detection and gait recognition method based on an improved twin neural network. The carried object detection and gait recognition method comprises the followingsteps: step 1, reading a front video and a rear video of entering and exiting a smart place; step 2, respectively synthesizing gait energy diagrams of the front-segment video and the rear-segment video by utilizing a gait energy diagram optimization synthesis method based on gravity center alignment; step 3, carrying object detection and gait recognition are carried out by using an improved twinneural network. Compared with a traditional gait recognition algorithm, the carrier detection and gait recognition method based on the improved twin neural network has the advantages that the gait recognition accuracy is effectively improved; meanwhile, whether the state of the same person is changed or not and whether the state of the same person is changed or not can be judged at the same time,and the judgment accuracy reaches 87.54%; furthermore, two problems are judged at the same time by using one network, so that the identification time is saved while the identification accuracy is ensured.

Description

technical field [0001] The invention relates to the field of image processing and computer vision research, in particular to a method for carrying object detection and gait recognition based on an improved twin neural network. Background technique [0002] With the progress of society and the development of science and technology, the application of intelligent video surveillance in the field of computer vision is becoming more and more extensive, and intelligent surveillance technology is also flourishing and changing with each passing day. At present, video surveillance technology has been widely used in various public places. With the advancement of technology and the reduction of costs, video surveillance technology will gradually enter the home, and there will be greater development in home security and home entertainment applications. [0003] The detection of objects carried by pedestrians is an important part of the research in the field of intelligent monitoring. It...

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Application Information

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IPC IPC(8): G06K9/00G06N3/04
CPCG06V40/25G06V40/10G06N3/045Y02T10/40
Inventor 渠慎明刘珊孙琳刘煊郭念王倩渠梦遥葉奕成
Owner HENAN UNIVERSITY