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Child detection frame filtering algorithm based on grid clustering

A grid clustering and filtering algorithm technology, applied in the field of computer vision, can solve problems such as insufficient sample size of children, incomplete pedestrians, and judgment of whether they are children

Active Publication Date: 2021-09-07
上海数川数据科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] 1. Due to pedestrian occlusion, the pedestrian in the detection frame is incomplete, and it is impossible to directly judge whether it is a child based on the size of the detection frame;
[0007] 2. Due to camera distortion, the frame size of the same person in different geographical locations is quite different;
[0008] 3. The sample size of children in the real scene is insufficient to participate in model training on a large scale

Method used

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  • Child detection frame filtering algorithm based on grid clustering

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Effect test

Embodiment 1

[0030] A kind of child detection frame filtering algorithm based on grid clustering, its method comprises the steps:

[0031] (1) Obtaining the image to be detected: the video data in the real scene is obtained through the camera, the camera sends the video data to the computer, obtains the target image and saves it, the computer recognizes the target object from the video data, and takes pictures of the target object, After obtaining the target image, a clearer target image can be obtained by screening, which is beneficial to extract the detection frame;

[0032] (2) Humanoid detection frame extraction: select the target camera, and pull the corresponding week’s detection frame data [xmin, ymin, xmax, ymax] from the production environment. The detection frame data corresponds to the coordinates of the upper left corner and right corner of the target image respectively The coordinates of the lower corner, the origin of the coordinates of the detection frame data is the upper l...

Embodiment 2

[0037] A kind of child detection frame filtering algorithm based on grid clustering, its method comprises the steps:

[0038] (1) Obtaining the image to be detected: the video data in the real scene is obtained through the camera, the camera sends the video data to the computer, obtains the target image and saves it, the computer recognizes the target object from the video data, and takes pictures of the target object, After obtaining the target image, a clearer target image can be obtained by screening, which is beneficial to extract the detection frame;

[0039] (2) Humanoid detection frame extraction: select the target camera, and pull the corresponding week’s detection frame data [xmin, ymin, xmax, ymax] from the production environment. The detection frame data corresponds to the coordinates of the upper left corner and right corner of the target image respectively The coordinates of the lower corner, the origin of the coordinates of the detection frame data is the upper l...

Embodiment 3

[0044] A kind of child detection frame filtering algorithm based on grid clustering, its method comprises the steps:

[0045](1) Obtaining the image to be detected: the video data in the real scene is obtained through the camera, the camera sends the video data to the computer, obtains the target image and saves it, the computer recognizes the target object from the video data, and takes pictures of the target object, After obtaining the target image, a clearer target image can be obtained by screening, which is beneficial to extract the detection frame;

[0046] (2) Humanoid detection frame extraction: select the target camera, and pull the corresponding week’s detection frame data [xmin, ymin, xmax, ymax] from the production environment. The detection frame data corresponds to the coordinates of the upper left corner and right corner of the target image respectively The coordinates of the lower corner, the origin of the coordinates of the detection frame data is the upper le...

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Abstract

The invention relates to the technical field of computer vision, in particular to a child detection frame filtering algorithm based on grid clustering, and the method comprises the following steps: obtaining video data in a real scene through a camera, transmitting the video data to a computer through the camera, obtaining a target image, storing the target image, selecting a target camera, and pulling detection frame data corresponding to one week from a production environment; according to the child detection frame filtering algorithm provided by the invention, a detected human-shaped frame can be directly used as statistical data, then the average frame height in the grid range is obtained by using a grid clustering method, whether a child is a child is judged by using the average frame height and the target frame height, and meanwhile, the average frame height of each region in a target image can be judged; misjudgment caused by shielding is avoided, and the problem that due to the fact that many shielding and false detection exist in a real scene, statistical clustering is directly carried out through a detection frame, the whole data distribution is disturbed by an abnormal detection frame, and consequently many misjudgments of a child frame are caused is solved.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a child detection frame filtering algorithm based on grid clustering. Background technique [0002] Object detection is one of the most fundamental problems in the field of computer vision and has been widely discussed and studied. In recent years, object detection methods based on deep convolutional neural networks have greatly improved the detection accuracy, but there are still many challenges in practical applications. For example, in some specific business scenarios (for example, the shopping mall passenger flow system analyzes user purchasing power behavior based on target detection) the detection system is required to be able to distinguish between "adults" and "children", that is, each human-shaped frame needs to be given a label to judge the person in the frame. Whether the character is an adult is convenient for making filter conditions for subsequent statistic...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06F18/23213
Inventor 林宇潘卿波赵宇迪施侃
Owner 上海数川数据科技有限公司
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