CN113297882A - Intelligent morning check robot, height measuring method and application - Google Patents
Intelligent morning check robot, height measuring method and application Download PDFInfo
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- 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
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- G06V10/40—Extraction of image or video features
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- G06V10/20—Image preprocessing
- G06V10/24—Aligning, centring, orientation detection or correction of the image
- G06V10/247—Aligning, centring, orientation detection or correction of the image by affine transforms, e.g. correction due to perspective effects; Quadrilaterals, e.g. trapezoids
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Abstract
The invention discloses an intelligent morning examination robot, a height measuring method and application. The height measuring method comprises the following steps: calibrating data of a camera; standing a person to be detected at a first designated position; the method comprises the following steps of acquiring the weight of a person to be detected, triggering a camera to acquire face image data of the person to be detected and carrying out face recognition; data transmission; acquiring the top position of the face of the person to be detected by using an opencv open source library; calculating the height; and displaying the height and weight results. The height measuring method is applied to the intelligent morning examination robot, is high in measuring efficiency and accurate in detection, facilitates simplification of equipment structure and reduction of size, and facilitates pushing the intelligent morning examination robot to quickly replace a traditional manual morning examination mode of a kindergarten.
Description
Technical Field
The invention relates to the field of robot equipment, in particular to an intelligent morning inspection robot, a height measuring method and application.
Background
Currently, there are many methods for measuring height, and the simplest method is to use a ruler to directly measure, and the measuring method needs manual operation to read data. An improved measuring method is that a movable cross rod is added on a vertical mark post, the up-and-down movement is controlled by a motor, and the cross rod stops when touching the top of the head in the moving process, so that the height of a human body is obtained.
With the gradual digital development of the measurement technology, a method for measuring the height of a human body by using ultrasonic waves appears, the height is measured by the time difference after the reflected echo of a measured object is received, and the measurement can be realized only by placing an ultrasonic transmitter at the top of the head. In addition, a method for measuring the height door by infrared is provided, but mechanical equipment is heavy, is not easy to move, has high cost, and can obtain accurate height only by forming a row by infrared. The height measuring method provided by the invention is integrated in intelligent equipment, only one camera is needed, the picture can be automatically acquired through the camera, the height of a person in the picture can be automatically calculated, the cost is low, the automation is realized, and the labor cost is saved.
Disclosure of Invention
The invention aims to provide a convenient and quick height measuring method with low cost, which is applied to an intelligent morning inspection robot to reduce the manufacturing cost and improve the detection efficiency and accuracy.
An intelligent morning check robot further comprises an oral cavity temperature measuring and herpes detecting system, a one-way trigger module, a weight sensor, a camera and user interaction display equipment which are electrically connected with each other; when the weight sensor senses the weight information of the person to be detected, the one-way trigger module triggers the oral cavity temperature measurement and herpes detection system to measure the temperature and trigger the camera to carry out face recognition and face image acquisition, the height of the person to be detected is obtained through the acquired face image calculation, and finally the height, weight and body temperature information are simultaneously displayed on the user interaction display device.
A height measurement method, comprising the steps of:
step 1: calibrating data of a camera;
step 2: a person to be detected stands at a first designated position and faces the camera;
step 3: the method comprises the following steps of acquiring the weight of a person to be detected, triggering a camera to acquire face image data of the person to be detected and carrying out face recognition;
step 4: data transmission;
step 5: acquiring the top position of the face of the person to be detected by using an opencv open source library;
step 6: calculating the height;
step 7: and (6) displaying the result.
Further, Step 11: fixing the position of the camera;
step 12: preparing a specific scale, and placing the specific scale at a first designated position, perpendicular to the horizontal ground and facing the camera;
step 13: starting the camera to shoot the picture of the specific scale;
step 14: performing distortion correction on the picture of the specific scale;
step 15: and (4) data storage.
Further, contain the scale zero line on the specific scale, set up the circle of vertical arranging above the scale zero line, set up a plurality of scale scales below the zero scale.
Further, the method for performing distortion correction on the picture in Step14 specifically includes:
step 141: converting the picture of the specific scale into an eight-bit single channel by an ARGB channel from eight to four channels;
step 142: performing binary conversion on the picture obtained by Step141 by an Otus algorithm;
step 143: detecting the outline of the circle on the specific scale by utilizing outline detection, and filtering other interference areas by utilizing the outline area and the characteristics of the circles vertically arranged on the scale;
step 144: fitting all the outlines of the circles into an ellipse by ellipse fitting, taking the average value of the major axis and the minor axis as the diameter of the circle, and taking the intersection point of the major axis and the minor axis as the center of the circle after fitting.
Further, Step15 stores data of the actual height of the center of the circle at the first designated position relative to the horizontal ground and the pixel height of the picture with the center at the specific scale.
Further, the method for calculating the height in Step6 includes:
firstly, judging that the vertex pixel point of the vertex position of the human face of the person to be detected obtained in the step5 is positioned between an upper circle and a lower circle which are adjacent;
calculating the actual vertical distance and the pixel vertical distance between the centers of the adjacent upper and lower circles;
calculating the height of the person to be detected by using the following calculation formula:
height = lower center of circle actual height + [ actual vertical distance between two adjacent upper and lower centers of circle/vertical distance of pixel between two adjacent upper and lower circles ] [ height of overhead pixel-height of lower center of circle pixel ].
Further, in the Step2, the triggering time is 2-6 seconds.
The invention also provides a height measuring method applied to the intelligent morning examination robot for height measurement.
Further, the first designated position in Step2 is a calibration measurement position of the intelligent morning examination robot, and is disposed above the weight sensor.
Compared with the prior art, the height measuring method provided by the invention is applied to the intelligent morning inspection robot and has the following beneficial effects:
use cost is low, has simplified intelligence is the robot equipment of examining morning, height weight measurement can be accomplished in weight inductor and trigger switch in coordination to a ordinary camera, thereby makes intelligence is examined robot hardware structure more simple, the weight is lighter, is convenient for carry morning.
Innovation in measurement mode: step2, standing the person to be detected at the first designated position of the intelligent morning inspection robot, namely, automatically triggering the camera of the intelligent morning inspection robot in the Step3 through the induction of a weight inductor arranged at the first designated position to acquire the face image data of the person to be detected, so that the standby time is reduced, and the energy consumption is saved.
The processing speed is high, the algorithm is simple, and the height of the person to be detected can be automatically calculated within 0.3S after the camera shoots the face image data of the person to be detected.
Drawings
FIG. 1 is a preferred embodiment of an intelligent morning check robot applying the height measuring method of the present invention;
FIG. 2 is a schematic diagram of the intelligent morning inspection robot provided in FIG. 1;
FIG. 3 is a flow chart of a height measurement method applied to the intelligent morning examination robot shown in FIG. 1;
FIG. 4 is a schematic structural diagram of a specific scale of a preferred embodiment of the height measuring method according to the present invention;
FIG. 5 is a flow chart of data calibration in a preferred embodiment of the height measurement method of the present invention;
FIG. 6 is a flow chart of a method for correcting image distortion in a preferred embodiment of the height measuring method according to the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments that can be derived by one skilled in the art from the embodiments given herein are intended to be within the scope of the invention.
The terms "comprises" and "comprising," and any variations thereof, in the description and claims of this invention and the above-described drawings are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Referring to fig. 1 and fig. 2, fig. 1 is a preferred embodiment of an intelligent morning check robot applying the height measuring method of the present invention; fig. 2 is a working principle diagram of the intelligent morning check robot provided in fig. 1. The intelligent morning examination robot 1 comprises a robot head 2, a robot body 3, a robot base 4, an oral cavity temperature measurement and herpes detection system 11, a camera 12, a weight sensor 13, a face recognition module 14, user interaction display equipment 15, a main control module 16 and a one-way trigger module 17.
The robot head 2, the robot body 3 and the robot base 4 are arranged from top to bottom in sequence.
The camera 12 is used for acquiring face image data of a person to be detected and transmitting the data to the face recognition module 14, the cloud server and the main control module 16. Weight inductor 13 locates robot base 4 for acquire the weight information of examining the person and transmit to main control module 16. The face recognition module 14 receives the face image data of the person to be detected and compares the face image data with data in the cloud server, if the face image data in the cloud server is recognized, the measured data is stored under a directory of the face image data, otherwise, the face image data is stored and addition of setting information is prompted. In the specific implementation process, the setting information under the face image comprises a series of user information such as name, gender, age, class and the like. The user interaction display device 15 is configured to obtain an interaction record of a user, and store the interaction record in a cloud server.
The one-way trigger module 17 and the weight sensor 13 are arranged on the robot base 4. The first designated position described in Step2 is placed above the weight sensor 13, in the embodiment by setting up a measurement flag on the weight scale containing the weight sensor 13. The specific working principle of the intelligent morning inspection robot 1 is as follows: when waiting to examine the personnel stand in the first assigned position of robot base 4, weight sensor 13 senses the moment of waiting to examine personnel's weight information, one-way trigger module 17 triggers oral cavity temperature measurement and herpes detecting system 11 carries out oral cavity temperature measurement and herpes and detects, triggers simultaneously camera 12 carries out face image data acquisition, and face identification module 14 carries out face identification, main control module 16 embeds height calculation module obtains waiting to examine personnel's height through the calculation. Finally, height, weight, body temperature, presence or absence of herpes are displayed simultaneously on said user interactive display device 15. For a specific body temperature measurement method and principle, please refer to the patent names applied by my company as follows: an intelligent morning check robot based on oral thermometry (201920435113.2). The triggering time in the scheme is preferably 2-6 seconds, if the triggering time is more than 6S, the camera 12 is ended, energy consumption waste is avoided, and when the triggering time is less than 2S, various measurements are not started due to the fact that the corresponding triggering time is short. See patent names applied by my company for herpes measurement: an intelligent morning check robot based on oral thermometry (201920435113.2). In a specific implementation process, the unidirectional trigger module 17 may be a hardware module or a software module, the hardware module may be but is not limited to a unidirectional trigger transistor, that is, a unidirectional switch, and the software module may be a program module configured to trigger the camera to start to operate after receiving the weight signal.
Referring to fig. 3, fig. 3 is a flowchart of a height measuring method applied to an intelligent morning inspection robot. The method specifically comprises the following steps:
step 1: calibrating data of the camera 12;
step 2: a person to be detected stands at a first designated position of the intelligent morning inspection robot 1 and faces the camera 12;
step 3: the weight of the person to be detected is obtained, meanwhile, the camera 12 is triggered to obtain the face image data of the person to be detected, and face recognition is carried out;
step 4: data transmission;
step 5: acquiring the top position of the face of the person to be detected by using an opencv open source library;
step 6: calculating the height;
step 7: the result is displayed on the user interactive display device 15.
Please refer to fig. 4, fig. 4 is a schematic structural diagram of a specific scale of a preferred embodiment of the height measuring method according to the present invention. Contain the scale zero line on the specific scale, set up the circle of vertical arranging above the scale zero line, set up a plurality of scale scales below the scale zero line. The special scale can be a special zip-top treasure with scales, the length of the scale can be freely stretched within a certain range, the length above the zero line of the scales is fixed and is generally about 60-80cm, and the scales arranged below the zero line of the scales are beneficial to calculating the actual height of the circle center, namely the sum of the length above the zero line of the scales and the length below the zero line of the scales. In the specific implementation process, the circles can not be randomly arranged on the same straight line, and only do not need to be overlapped so as to be distinguished conveniently. In a specific implementation process, the circle can be replaced by a regular polygon or other regular-shaped figures, but the figure distortion correction of the figures with other shapes is more difficult than that of the circle.
Please refer to fig. 5, which is a flowchart illustrating a data calibration process according to a preferred embodiment of the present invention. The purpose of this step is to obtain the actual height of each circle center on the specific scale relative to the horizontal ground at the first designated position and the pixel height of the picture with the circle center on the specific scale. In the using process, the position and the angle of the camera 12 on the intelligent morning examination robot 1 are ensured to be the same as those in data calibration.
The specific data calibration implementation steps are as follows:
step 11: fixing the position of the camera 12 on the intelligent morning examination robot 1;
step 12: preparing a specific scale, and placing the specific scale at a first designated position, perpendicular to the horizontal ground, facing the camera 12;
step 13: starting the camera 12 to take a picture of the specific scale;
step 14: carrying out distortion correction on the picture of the specific scale;
step 15: and (4) data storage.
Please refer to fig. 6, which is a flowchart illustrating a method for correcting image distortion in a preferred embodiment of a height measurement method applied to an intelligent morning examination robot. By distortion correction, measurement accuracy is achieved while reducing dependency on hardware. The specific technical scheme is as follows:
step 141: converting the obtained picture of the specific scale into an eight-bit single-channel picture through an ARGB channel eight-bit four-channel picture;
step 142: performing binary conversion on the picture of the specific scale through an Otus algorithm;
step 143: detecting the outline of a circle on the specific scale by utilizing outline detection, and filtering other interference areas by utilizing the outline area and the characteristics of the circles vertically arranged on the scale;
step 144: and fitting the outlines of all circles of the specific scale into an ellipse by ellipse fitting, taking the average value of the major axis and the minor axis of the ellipse as the diameter of the circle, and taking the intersection point of the major axis and the minor axis as the center of the fitted circle.
In the invention, other interference regions are filtered by the two characteristics of the area of the outline of the circle on the specific scale and the vertical arrangement of a plurality of circles.
Specifically, the method for calculating the height in Step6 includes:
firstly, judging that the vertex pixel point of the vertex position of the human face of the person to be detected obtained in the step5 is positioned between an upper circle and a lower circle which are adjacent;
calculating the actual vertical distance and the pixel vertical distance between the centers of the adjacent upper and lower circles;
calculating the height of the person to be detected by using the following calculation formula:
height = lower center of circle actual height + [ actual vertical distance between two adjacent upper and lower centers of circle/vertical distance of pixel between two adjacent upper and lower circles ] [ height of overhead pixel-height of lower center of circle pixel ].
OpenCV is a BSD license (open source) based distributed cross-platform computer vision library that can run on Linux, Windows, Android, and Mac OS operating systems. The method is light and efficient, is composed of a series of C functions and a small number of C + + classes, provides interfaces of languages such as Python, Ruby, MATLAB and the like, and realizes a plurality of general algorithms in the aspects of image processing and computer vision. In the invention, the FindContours function algorithm in opencv is used for detecting the contour of the circle.
The Otsu algorithm (Otsu method or maximum inter-class variance method) is the optimal algorithm for selecting the threshold in image segmentation, is simple in calculation and is not influenced by the brightness and the contrast of an image, the idea of clustering is used, the gray level number of the image is divided into 2 parts according to the gray level, the gray level difference between the two parts is maximum, the gray level difference between each part is minimum, and a proper gray level is searched through the variance calculation for division. The Otsu algorithm can be used to automatically select the threshold value for binarization during binarization. Thus, a segmentation that maximizes the inter-class variance means that the probability of false positives is minimized.
The height measurement protocol provided by the invention comprises a method, a device, a system and/or a computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therein for carrying out aspects of the present invention.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present invention may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present invention are implemented by personalizing an electronic circuit, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA), with state information of computer-readable program instructions, which can execute the computer-readable program instructions.
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Compared with the prior art, the height measuring method provided by the invention is applied to the intelligent morning inspection robot 1 and has the following beneficial effects:
use cost is low, has simplified intelligence morning examines robot 1 equipment, and height measurement can be accomplished in cooperation weight inductor 13 and trigger switch to a ordinary camera 12 to make intelligence morning examines robot 1 weight lighter, the transport of being convenient for.
Innovation in measurement mode: step2, standing the person to be detected at the first designated position of the intelligent morning inspection robot 1, namely, automatically triggering the camera 12 of the intelligent morning inspection robot 1 in the Step3 through the induction of the weight inductor 13 arranged at the first designated position to acquire the face image data of the person to be detected, so that the standby time is reduced, and the energy consumption is saved.
The processing speed is high, and the height of the person to be detected can be automatically calculated within 0.3S after the camera 12 shoots the face image data of the person to be detected.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An intelligent morning check robot is characterized by comprising an oral cavity temperature measuring and herpes detecting system, a one-way trigger module, a weight sensor, a camera and user interaction display equipment which are electrically connected with each other; when the weight sensor senses the weight information of the person to be detected, the one-way trigger module triggers the oral cavity temperature measurement and herpes detection system to measure the temperature and trigger the camera to carry out face recognition and face image acquisition, the height of the person to be detected is obtained through the acquired face image calculation, and finally the height, the weight, the body temperature and the herpes information are simultaneously displayed on the user interaction display device.
2. A height measuring method is characterized by comprising the following steps:
step 1: calibrating data of a camera;
step 2: a person to be detected stands at a first designated position and faces the camera;
step 3: the method comprises the following steps of acquiring the weight of a person to be detected, triggering a camera to acquire face image data of the person to be detected and carrying out face recognition;
step 4: data transmission;
step 5: acquiring the top position of the face of the person to be detected by using an opencv open source library;
step 6: calculating the height;
step 7: and (6) displaying the result.
3. The height measurement method according to claim 2, wherein Step1 further comprises the steps of:
step 11: fixing the position of the camera;
step 12: preparing a specific scale, and placing the specific scale at a first designated position, perpendicular to the horizontal ground and facing the camera;
step 13: starting the camera to shoot the picture of the specific scale;
step 14: performing distortion correction on the picture of the specific scale;
step 15: and (4) data storage.
4. The height measuring method according to claim 3, wherein the specific scale comprises a zero line, a vertically arranged circle is disposed above the zero line, and a plurality of scale marks are disposed below the zero line.
5. The height measurement method according to claim 4, wherein the Step of correcting distortion of the picture in Step14 comprises:
step 141: converting the picture of the specific scale into an eight-bit single channel by an ARGB channel from eight to four channels;
step 142: performing binary conversion on the picture obtained by Step141 by an Otus algorithm;
step 143: detecting the outline of the circle on the specific scale by utilizing outline detection, and filtering other interference areas by utilizing the outline area and the characteristics of the circles vertically arranged on the scale;
step 144: fitting all the outlines of the circles into an ellipse by ellipse fitting, taking the average value of the major axis and the minor axis as the diameter of the circle, and taking the intersection point of the major axis and the minor axis as the center of the circle after fitting.
6. The height measurement method according to claim 5, wherein Step15 stores data comprising the actual height of the center of all said circles on said specific scale relative to the horizontal ground at said first designated position and the pixel height of the picture centered on said specific scale.
7. The height measuring method according to claim 6, wherein the height calculating Step6 comprises:
firstly, judging that the vertex pixel point of the vertex position of the human face of the person to be detected obtained in the step5 is positioned between an upper circle and a lower circle which are adjacent;
calculating the actual vertical distance and the pixel vertical distance between the centers of the adjacent upper and lower circles;
calculating the height of the person to be detected by using the following calculation formula:
height = lower center of circle actual height + [ actual vertical distance between two adjacent upper and lower centers of circle/vertical distance of pixel between two adjacent upper and lower circles ] [ height of overhead pixel-height of lower center of circle pixel ].
8. The height measurement method according to claim 7, wherein the triggering time of Step2 is 2-6 seconds.
9. Use of a height measurement method according to claim 8 in an intelligent morning check robot according to claim 1.
10. The use of claim 9, wherein the first designated position in Step2 is a calibrated measurement position of the intelligent morning examination robot, which is disposed above the weight sensor.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113873119A (en) * | 2021-09-22 | 2021-12-31 | 深圳百岁欢智能科技有限公司 | Science and technology detection method based on medical robot |
| CN114485884A (en) * | 2022-01-25 | 2022-05-13 | 山东爱升信息科技有限公司 | Infrared-free weight and height measuring device and method based on fixed edge |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107280118A (en) * | 2016-03-30 | 2017-10-24 | 深圳市祈飞科技有限公司 | A kind of Human Height information acquisition method and the fitting cabinet system using this method |
| US20180089501A1 (en) * | 2015-06-01 | 2018-03-29 | Unifai Holdings Limited | Computer implemented method of detecting the distance of an object from an image sensor |
| CN208432335U (en) * | 2018-07-30 | 2019-01-25 | 赵晓慧 | A kind of hand-held Intelligence In Baogang Kindergarten morning inspection instrument |
| CN109464132A (en) * | 2019-01-11 | 2019-03-15 | 肖湘江 | Robot, kindergarten morning check system |
| CN110097596A (en) * | 2019-04-30 | 2019-08-06 | 湖北大学 | A kind of object detection system based on opencv |
-
2020
- 2020-06-23 CN CN202010578411.4A patent/CN113297882A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180089501A1 (en) * | 2015-06-01 | 2018-03-29 | Unifai Holdings Limited | Computer implemented method of detecting the distance of an object from an image sensor |
| CN107280118A (en) * | 2016-03-30 | 2017-10-24 | 深圳市祈飞科技有限公司 | A kind of Human Height information acquisition method and the fitting cabinet system using this method |
| CN208432335U (en) * | 2018-07-30 | 2019-01-25 | 赵晓慧 | A kind of hand-held Intelligence In Baogang Kindergarten morning inspection instrument |
| CN109464132A (en) * | 2019-01-11 | 2019-03-15 | 肖湘江 | Robot, kindergarten morning check system |
| CN110097596A (en) * | 2019-04-30 | 2019-08-06 | 湖北大学 | A kind of object detection system based on opencv |
Non-Patent Citations (1)
| Title |
|---|
| 尹汪: "基于图像的人体尺寸获取", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113873119A (en) * | 2021-09-22 | 2021-12-31 | 深圳百岁欢智能科技有限公司 | Science and technology detection method based on medical robot |
| CN114485884A (en) * | 2022-01-25 | 2022-05-13 | 山东爱升信息科技有限公司 | Infrared-free weight and height measuring device and method based on fixed edge |
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