People counting method and device

A technology of people counting and position coordinates, which is applied in the field of image processing, can solve the problems of difficult end-to-end target detection, reduce the real-time performance of people counting, etc., and achieve the effect of improving accuracy, increasing speed, and increasing training speed

Active Publication Date: 2021-06-22
济南宇视智能科技有限公司
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AI Technical Summary

Problems solved by technology

[0003] However, most of the existing neural network-based people counting methods use the target detection idea of ​​"area proposal box and classifier". real-time

Method used

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  • People counting method and device

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Embodiment Construction

[0024] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.

[0025] The terminology used in this application is for the purpose of describing particular embodiments only, and is not intended to limit the application. As used in this application and the appended claims, the singular forms "a", "the", and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the term...

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Abstract

The present application provides a people counting method and device, the method is applied to a server equipped with a people counting model including an image feature extraction sub-model based on a convolutional neural network and an SSD classification regression sub-model, specifically including: inputting an image frame into an image The feature extraction sub-model generates an image feature map; based on the SSD classification regression sub-model, a default box is generated for each pixel in the image feature map, and the position coordinates and probability scores of each default box are obtained, and the maximum probability score is used as the primary confidence; The top K default boxes with the highest confidence are used as target candidate boxes; based on the position coordinates and probability scores of each target candidate box, bounding box regression analysis and softxmax classification are performed to obtain the coordinate position and final confidence of each target candidate box; based on non- The maximum value suppression algorithm obtains the target frame, and counts the number of people in the monitoring area based on the number of target frames. Using this method can effectively improve the real-time performance of people counting.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular to a method and device for counting people. Background technique [0002] With the development of computer vision, video surveillance technology is becoming more and more important in ensuring public safety and maintaining social stability. People counting is an important part of the video surveillance field. Real-time and effective people counting provides basic data for crowd behavior analysis and plays an important role in preventing crowd congestion and illegal gatherings. [0003] However, most of the existing neural network-based people counting methods use the target detection idea of ​​"area proposal box and classifier". real-time. Contents of the invention [0004] In view of this, the present application provides a method and device for counting people to improve the real-time performance of counting people. [0005] Specifically, this application i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/02
CPCG06N3/02G06V20/53G06F18/241
Inventor 徐茜毛泉涌祝中科王玲陈艳良
Owner 济南宇视智能科技有限公司
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