CN113095461A - Pull-up counter based on machine vision - Google Patents
Pull-up counter based on machine vision Download PDFInfo
- Publication number
- CN113095461A CN113095461A CN202110398457.2A CN202110398457A CN113095461A CN 113095461 A CN113095461 A CN 113095461A CN 202110398457 A CN202110398457 A CN 202110398457A CN 113095461 A CN113095461 A CN 113095461A
- Authority
- CN
- China
- Prior art keywords
- module
- counting
- chin
- monocular camera
- pull
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 240000007651 Rubus glaucus Species 0.000 claims abstract description 21
- 235000011034 Rubus glaucus Nutrition 0.000 claims abstract description 21
- 235000009122 Rubus idaeus Nutrition 0.000 claims abstract description 21
- 238000000034 method Methods 0.000 claims abstract description 11
- 238000001514 detection method Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 4
- 238000013500 data storage Methods 0.000 claims description 2
- 238000012360 testing method Methods 0.000 description 9
- 230000000007 visual effect Effects 0.000 description 5
- 230000009471 action Effects 0.000 description 3
- 210000001015 abdomen Anatomy 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 239000011499 joint compound Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 210000001364 upper extremity Anatomy 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06M—COUNTING MECHANISMS; COUNTING OF OBJECTS NOT OTHERWISE PROVIDED FOR
- G06M1/00—Design features of general application
- G06M1/27—Design features of general application for representing the result of count in the form of electric signals, e.g. by sensing markings on the counter drum
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/207—Analysis of motion for motion estimation over a hierarchy of resolutions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/167—Detection; Localisation; Normalisation using comparisons between temporally consecutive images
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Human Computer Interaction (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a chin-up counter based on machine vision, which comprises a raspberry group module and a monocular camera, wherein a face recognition module is embedded in the monocular camera, a chin-up counting program is pre-installed in the raspberry group module, and the monocular camera is arranged at the horizontal height of a horizontal bar and is connected with the raspberry group module. The on-line counting function of the pull-up is realized by using an equipment combination of an embedded system (raspberry pi) and a monocular camera and by using a mode of combining face recognition and target tracking. The chin-up counter device based on machine vision uses an embedded system to replace a traditional PC platform, the prior face recognition method is optimized, and the face recognition and target tracking method is adopted, so that the chin-up counter device is simple in structure and convenient to arrange, reduces hardware cost and has high use value.
Description
Technical Field
The invention relates to a counting tool for a pull-up test, which aims at the problems that the test result is unfair and the existing pull-up test equipment has complex structure, poor interaction capability, high cost, difficult installation and maintenance cost and difficult laying due to large subjectivity and non-uniform standard during manual invigilation.
Background
The 'national student physical health standard' test requires that all students in junior high school and college need to perform the pull-up test every year, and is one of the important reference standards and items for measuring the male physical constitution.
The pull-up mainly tests the development level of upper limb muscle strength, arm strength and waist and abdomen strength, and is a multi-joint compound action. The traditional pull-up test needs manual invigilation, has high subjectivity and non-uniform standards, and is easy to have the phenomenon of unfairness of test results. Some intelligent test systems are also proposed, and can be classified into non-visual sensors such as ultrasonic sensors and visual sensors according to the type of sensors used. Wherein the non-visual sensor mainly judges the fixed position and the distance to have no good effect of the visual sensor on the dynamic action, the fixed numerical value is not fair to people with different height conditions and swinging actions, and most of equipment needs to be fixed at a specific position and is not easy to lay and install. Most current visual sensors use a combination of a similar kinect sensor and a PC (personal computer) to perform bone tracking or face recognition to realize the counting of the chin, but the hardware cost is high.
Disclosure of Invention
The invention aims to provide a pull-up counter based on machine vision, which has the advantages of simple structure, convenience in layout, capability of effectively reducing hardware cost while ensuring accuracy and higher use value compared with the existing counter at home and abroad.
The technical scheme of the invention is as follows: the utility model provides a chin up counter based on machine vision, includes raspberry group module and monocular camera, and the embedding has face identification module in the monocular camera, and preinstall has the chin up counting procedure in the raspberry group module, and the monocular camera is laid at the horizontal bar level and is connected with raspberry group module.
The raspberry pi module comprises a data input module, a main controller, a data display module, an image processing module, a position detection module, a target tracking module and a counting module. The main controller is a core control unit and is used for controlling other modules, and the data input module, the data display module, the image processing module, the position detection module, the target tracking module and the counting module are all connected with the main controller; the data input module is used for inputting the face image collected by the single camera into the main controller for recognition, and the recognition result is displayed through the data display module. After a chin up-counting image acquired by the monocular camera passes through the data input module, the chin up-counting image is identified and calculated through the image processing module, the position detection module, the target tracking module and the counting module, and the chin up-counting image automatically counts the chin of the target identified by the human face.
In the counting procedure in the raspberry pi module, firstly, a school number is input, then confirm is clicked to start pull-up counting, and next data storage is clicked after counting is completed, so that the next round of counting process can be carried out.
The on-line counting function of the pull-up is realized by using an equipment combination of an embedded system (raspberry pi) and a monocular camera and by using a mode of combining face recognition and target tracking.
The invention has the advantages that: the chin-up counter equipment based on machine vision uses an embedded system to replace a traditional PC platform, the prior face recognition method is optimized, and the face recognition and target tracking method is adopted, so that the chin-up counter equipment is simple in structure and convenient to arrange, reduces hardware cost and has higher use value.
Drawings
Fig. 1 shows the overall system architecture.
Fig. 2 is an algorithm implementation flow.
FIG. 3 is a program home interface.
Fig. 4 is a program run-out interface.
Fig. 5 is a program restart count interface.
Detailed Description
In order to make the aforementioned and other features and advantages of the invention more comprehensible, embodiments accompanied with figures are described in detail below.
As shown in fig. 1-5, a chin-up counter based on machine vision comprises a raspberry pi module and a monocular camera, wherein a face recognition module is embedded in the monocular camera, a chin-up counting program is pre-installed in the raspberry pi module, and the monocular camera is arranged at the horizontal level of a horizontal bar and connected with the raspberry pi module. In a counting program in the raspberry group module, firstly, a school number is input, then confirm is clicked to start pull-up counting, next data is clicked to store after counting is finished, and then the next counting process can be carried out
The on-line counting function of the pull-up is realized by using an equipment combination of an embedded system (raspberry pi) and a monocular camera and by using a mode of combining face recognition and target tracking. And arranging the equipment in the drawing at the horizontal bar level, opening a built-in program, inputting a study number, clicking confirm to start pull-up counting, clicking next to store data after counting is finished, and then carrying out the next round of counting process.
Claims (3)
1. A pull-up counter based on machine vision, comprising: the raspberry type counting device comprises a raspberry group module and a monocular camera, wherein a face recognition module is embedded in the monocular camera, a pull-up counting program is pre-installed in the raspberry group module, and the monocular camera is arranged at the horizontal bar level and is connected with the raspberry group module.
2. The machine vision based pull-up counter of claim 1, wherein: the raspberry pi module comprises a data input module, a main controller, a data display module, an image processing module, a position detection module, a target tracking module and a counting module; the main controller is a core control unit and is used for controlling other modules, and the data input module, the data display module, the image processing module, the position detection module, the target tracking module and the counting module are all connected with the main controller; the data input module is used for inputting the face image acquired by the monocular camera into the main controller for recognition, and the recognition result is displayed through the data display module; after a chin up-counting image acquired by the monocular camera passes through the data input module, the chin up-counting image is identified and calculated through the image processing module, the position detection module, the target tracking module and the counting module, and the chin up-counting image automatically counts the chin of the target identified by the human face.
3. The machine vision based pull-up counter of claim 2, wherein: in the counting procedure in the raspberry pi module, firstly, a school number is input, then confirm is clicked to start pull-up counting, and next data storage is clicked after counting is completed, so that the next round of counting process can be carried out.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110398457.2A CN113095461A (en) | 2021-04-11 | 2021-04-11 | Pull-up counter based on machine vision |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110398457.2A CN113095461A (en) | 2021-04-11 | 2021-04-11 | Pull-up counter based on machine vision |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113095461A true CN113095461A (en) | 2021-07-09 |
Family
ID=76677062
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110398457.2A Pending CN113095461A (en) | 2021-04-11 | 2021-04-11 | Pull-up counter based on machine vision |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113095461A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116306766A (en) * | 2023-03-23 | 2023-06-23 | 北京奥康达体育产业股份有限公司 | Wisdom horizontal bar pull-up examination training system based on skeleton recognition technology |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111368791A (en) * | 2020-03-18 | 2020-07-03 | 南通大学 | Pull-up test counting method and system based on Quick-OpenPose model |
-
2021
- 2021-04-11 CN CN202110398457.2A patent/CN113095461A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111368791A (en) * | 2020-03-18 | 2020-07-03 | 南通大学 | Pull-up test counting method and system based on Quick-OpenPose model |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116306766A (en) * | 2023-03-23 | 2023-06-23 | 北京奥康达体育产业股份有限公司 | Wisdom horizontal bar pull-up examination training system based on skeleton recognition technology |
| CN116306766B (en) * | 2023-03-23 | 2023-09-22 | 北京奥康达体育产业股份有限公司 | Wisdom horizontal bar pull-up examination training system based on skeleton recognition technology |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| RU2617972C1 (en) | Simulator for operational and maintenance staff on the basis of virtual reality models of transformer substation | |
| CN105608467A (en) | Kinect-based non-contact type student physical fitness evaluation method | |
| CN107292778A (en) | A kind of cloud classroom learning evaluation method and its device based on cognitive emotion perception | |
| CN202601003U (en) | Test device for teaching quality evaluation in university | |
| CN107633261A (en) | A kind of fire architecture drawing intelligent checks system and method based on artificial intelligence | |
| CN109615723A (en) | Inspection route coverage condition automatic analysis method and system | |
| CN113095461A (en) | Pull-up counter based on machine vision | |
| CN111553229A (en) | Worker action identification method and device based on three-dimensional skeleton and LSTM | |
| CN203074671U (en) | Intelligent eye test device | |
| CN107818563A (en) | A kind of transmission line of electricity bundle spacing space measurement and localization method | |
| CN105426859A (en) | Intelligent monitoring and statistics system for use condition of school playground | |
| CN106657308A (en) | Campus sensing system based on smart bracelet | |
| CN114998986A (en) | Computer vision-based pull-up action specification intelligent identification method and system | |
| CN208212008U (en) | From survey formula vision inspection system | |
| CN103777754B (en) | Hand motion tracking device and method based on binocular infrared vision | |
| CN106708786A (en) | Method and system for calculating problem severity of iron tower based on sensor detection | |
| CN104091480A (en) | Transmission line condition-based maintenance simulation training method | |
| CN116369906A (en) | Automatic testing method, device, equipment and medium for arm bending suspension | |
| CN116099181A (en) | Upper limb strength training auxiliary system based on universe and application method thereof | |
| CN206729868U (en) | A kind of intelligent testing myopia system | |
| CN106390418B (en) | A kind of implementation method of ultrasonic wave chin-up test | |
| CN104460578B (en) | Intelligent agent positioning control system based on parallel control and control method thereof | |
| CN205139329U (en) | Module lithium cell testing arrangement | |
| CN113469113A (en) | Action counting method and device, electronic equipment and storage medium | |
| CN114011026A (en) | Non-contact physical ability test system and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |