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A CNN-based Barefoot Footprint Weight Determination Method

A judging method and weight technology, which is applied in the direction of instruments, calculations, character and pattern recognition, etc., can solve the problems of inconvenient portability, single function, and low degree of intelligence, and achieve the effect of improving accuracy and liberating manpower

Active Publication Date: 2021-06-18
DALIAN EVERSPRY SCI & TECH
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0002] Weight measurement is something that people often do in daily life. It is widely used in medical applications, school physical examinations, home applications and other fields. In the mid-1950s, the development of electronic technology promoted the rapid development of weight measurement manufacturing industry. The mechanical weight measuring instrument is not easy to carry, has a single function, low measurement accuracy and low intelligence, and the measurement is greatly affected by temperature changes. Therefore, further research on the measurement method of body weight has very practical significance

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  • A CNN-based Barefoot Footprint Weight Determination Method
  • A CNN-based Barefoot Footprint Weight Determination Method
  • A CNN-based Barefoot Footprint Weight Determination Method

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Embodiment 1

[0074] This embodiment provides a weight determination method based on CNN-based barefoot footprints, including:

[0075] S1: Obtain image data of barefoot footprints, and preprocess the image data;

[0076] S2: Create a barefoot image dataset;

[0077] 1) Divide the preprocessed barefoot image dataset into two parts:

[0078] (1) Training set: used for the training process of deep learning, each barefoot footprint data sample has subordinate weight information, and this weight information is the label of the barefoot footprint;

[0079] (2) Verification set: used to verify the quality of deep learning results. Each barefoot footprint data sample has subordinate weight information, but the validation set does not participate in training, and is only used to measure the accuracy of weight determination.

[0080] 2) Among them, the data requirements of each part:

[0081] (1) The data dimension of the verification set shall not be higher than that of the training set data, a...

Embodiment 2

[0140] This embodiment is as a further supplement to embodiment 1,

[0141] Step S1: Acquire barefoot footprint image data, and preprocess the image data, specifically:

[0142] 1) Barefoot footprint image data acquisition:

[0143] (1) Dynamic barefoot footprint data: This type of data is real-time barefoot footprint data collected through collection equipment, which reflects the state of barefoot footprint at a certain moment, and can better reflect the changes of barefoot footprint every moment;

[0144] (2) Static barefoot footprint data: The data is the average state of the barefoot footprint collected by the collection equipment within a certain period of time, which reflects the balance state of the overall sole of the foot, and can better reflect the stable characteristics of the objective barefoot footprint.

[0145] Among them, the barefoot footprint data includes but not limited to one-dimensional pressure trajectory data, two-dimensional real-time dynamic barefoot...

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Abstract

The invention discloses a CNN-based weight determination method for barefoot or sock-wearing footprints, comprising: S1: acquiring barefoot or sock-wearing footprint image data, and preprocessing the image data; S2: making a barefoot image data set; S3: Data training and feature extraction: S4: Weight determination. This application uses deep learning to realize the estimation of human body weight. While liberating manpower, the accuracy of judgment has also been greatly improved.

Description

technical field [0001] The invention relates to a weight judging method, in particular to a CNN-based barefoot footprint weight judging method. Background technique [0002] Weight measurement is something that people often do in daily life. It is widely used in medical applications, school physical examinations, home applications and other fields. In the mid-1950s, the development of electronic technology promoted the rapid development of weight measurement manufacturing industry. Mechanical weight measuring instruments are not easy to carry, have a single function, low measurement accuracy and low intelligence, and the measurement is greatly affected by temperature changes. Therefore, further research on the measurement method of body weight has very practical significance. Contents of the invention [0003] This application provides a CNN-based weight determination method based on barefoot footprints, which uses deep learning to estimate human body weight. While liberat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/10G06F18/214G06F18/24
Inventor 郭宝珠张吉昌于昕晔
Owner DALIAN EVERSPRY SCI & TECH
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