BMI evaluation method and device and computer readable storage medium

An evaluation method, a technology to be tested, applied in computer components, computer-aided medical programs, calculations, etc., can solve the problems of slow measurement, cumbersome use of procedures, time-consuming and labor-intensive, etc., and achieve the effect of reducing the difficulty of measurement

Pending Publication Date: 2019-04-16
PING AN TECH (SHENZHEN) CO LTD
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Problems solved by technology

[0003] The traditional BMI acquisition method needs to measure the height and weight information of the subject first. This information needs to be carried out using a height and weight tester or other measurement sensors manually, and then numerical calculations are performed to obtain the final BMI index. Not only does it require a specific Instruments (usually such

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  • BMI evaluation method and device and computer readable storage medium
  • BMI evaluation method and device and computer readable storage medium
  • BMI evaluation method and device and computer readable storage medium

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[0054] It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0055] The invention provides a BMI evaluation method. Reference figure 1 As shown, figure 1 It is a schematic flowchart of a BMI evaluation method provided by an embodiment of the present invention. The method can be executed by a device, and the device can be implemented by software and / or hardware.

[0056] In this embodiment, the BMI evaluation method includes:

[0057] Step S10: Collect sample face image data, where the sample face image data includes a BMI value.

[0058] Step S20, using convolutional neural network training sample face image data to obtain a training model.

[0059] Specifically, an online server can collect 10,000 sample face images with BMI values, and train a convolutional neural network under the caffe deep learning framework.

[0060] The training of the convolutional neural network includes:...

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Abstract

The invention relates to the technical field of intelligent decision making, and discloses a BMI evaluation method, which comprises the following steps: collecting sample face image data, the sample face image data comprising a BMI value; training the sample face image data by adopting a convolutional neural network to obtain a training model; obtaining a to-be-detected face image, positioning face key feature points of the to-be-detected face image, and obtaining face key points; performing face contour extraction according to the face key points to obtain a face contour; performing equal-proportion stretching on the face contour according to a perspective view angle to obtain a preprocessed face image; and performing category prediction on the preprocessed face image according to the training model to obtain an evaluation BMI value of the face image to be detected. The invention further provides a BMI evaluation device and a computer readable storage medium. According to the invention, the BMI value can be rapidly detected in real time, and the BMI measurement difficulty of a measurer is reduced.

Description

technical field [0001] The invention relates to the technical field of intelligent decision-making, in particular to a BMI evaluation method, device and computer-readable storage medium. Background technique [0002] BMI index (body mass index, referred to as body mass index, also known as body mass index, English is Body Mass Index, referred to as BMI) is a parameter related to height and weight that can reflect body mass index / obesity index, which is divided by weight in kilograms The number obtained by the square of the height in meters. It is mainly used for statistics. When it is necessary to compare and analyze the health impact of a person's weight on people of different heights, the BMI value is a neutral and reliable indicator. It is commonly used internationally to measure the degree of body fat and thinness and whether it is healthy of a standard. BMI is an indicator closely related to total body fat, which takes into account two factors: weight and height. BMI...

Claims

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Application Information

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IPC IPC(8): G16H50/30G06K9/00G06K9/62
CPCG16H50/30G06V40/168G06V40/172G06F18/214
Inventor 石磊马进王健宗肖京
Owner PING AN TECH (SHENZHEN) CO LTD
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