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Attention level detection method and device, computing equipment and storage medium

A level detection and attention technology, applied in computing, computer components, neural learning methods, etc., can solve the problem of inaccurate evaluation results, and achieve the effect of accurate attention level and accurate evaluation

Pending Publication Date: 2021-04-02
BEIJING YINGPU TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Evaluation results are often inaccurate as only a single aspect is detected

Method used

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  • Attention level detection method and device, computing equipment and storage medium
  • Attention level detection method and device, computing equipment and storage medium
  • Attention level detection method and device, computing equipment and storage medium

Examples

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Embodiment Construction

[0041] figure 1 is a schematic flow chart of a method for detecting an attention level according to an embodiment of the present application. The method may generally include:

[0042] Step S1, using the SSIM algorithm to extract key frames from the video output by the monitoring device:

[0043] The monitoring equipment is used to capture videos of people, such as videos of students in classrooms, and high-quality cameras should be used to shoot videos, and light changes and shadows should be avoided;

[0044] The SSIM algorithm is used for video summarization and other video-related processing. The key frames are generated by the SSIM algorithm using visual features such as color histograms, moments, and correlation measures. The summary videos generated by this algorithm are close to human perception. The formula used by the SSIM algorithm is:

[0045] SSIM(x,y)=l(x,y).c(x,y).s(x,y)

[0046] where l(x,y) represents the change in brightness between image x and image y, c...

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Abstract

The invention discloses an attention level detection method and device, computing equipment and a storage medium. The method comprises the following steps of extracting a key frame from a video outputby monitoring equipment by adopting an SSIM algorithm, adopting a convolutional neural network to detect the sleepiness, the watching condition and the facial expression of the character in the key frame, and determining the attention level of the person in the video according to the sleepiness detection result, the facial expression detection result and the gaze condition detection result. The device comprises a key frame extraction module, a detection module and a judgment module. The computing equipmentincludes a memory, a processor, and a computer program stored within the memory and executable by the processor, where the processor implements the method described herein when executing the computer program. The storage medium is preferably a non-volatile readable storage medium, a computer program is stored in the storage medium, and the computer program implements the method when executed by the processor.

Description

technical field [0001] This application relates to the recognition of facial expressions of characters in video images, and in particular to the attention detection technology of characters in classrooms. Background technique [0002] A common way to assess student attention levels is to assess the body language of students in the classroom, including checking to see if the student is sleeping, whether the student has a happy expression during a lecture, and the direction the student is looking. Since only a single aspect is detected, the evaluation results are often inaccurate. Contents of the invention [0003] It is an object of the present application to overcome the above-mentioned problems or to at least partially solve or alleviate the above-mentioned problems. [0004] According to one aspect of the present application, a method for detecting attention level is provided, comprising: [0005] Using the SSIM algorithm to extract key frames from the video output by ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/174G06V20/52G06N3/045G06F18/22
Inventor 樊硕
Owner BEIJING YINGPU TECH CO LTD
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