CN111713806A - Insole matching method and system based on depth camera, intelligent terminal and storage medium - Google Patents
Insole matching method and system based on depth camera, intelligent terminal and storage medium Download PDFInfo
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- CN111713806A CN111713806A CN202010558532.2A CN202010558532A CN111713806A CN 111713806 A CN111713806 A CN 111713806A CN 202010558532 A CN202010558532 A CN 202010558532A CN 111713806 A CN111713806 A CN 111713806A
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- A—HUMAN NECESSITIES
- A43—FOOTWEAR
- A43D—MACHINES, TOOLS, EQUIPMENT OR METHODS FOR MANUFACTURING OR REPAIRING FOOTWEAR
- A43D1/00—Foot or last measuring devices; Measuring devices for shoe parts
- A43D1/02—Foot-measuring devices
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- A—HUMAN NECESSITIES
- A43—FOOTWEAR
- A43D—MACHINES, TOOLS, EQUIPMENT OR METHODS FOR MANUFACTURING OR REPAIRING FOOTWEAR
- A43D1/00—Foot or last measuring devices; Measuring devices for shoe parts
- A43D1/02—Foot-measuring devices
- A43D1/022—Foot-measuring devices involving making footprints or permanent moulds of the foot
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- A—HUMAN NECESSITIES
- A43—FOOTWEAR
- A43D—MACHINES, TOOLS, EQUIPMENT OR METHODS FOR MANUFACTURING OR REPAIRING FOOTWEAR
- A43D1/00—Foot or last measuring devices; Measuring devices for shoe parts
- A43D1/02—Foot-measuring devices
- A43D1/027—Shoe fit indicating devices
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
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Abstract
The invention relates to a shoe pad matching method based on a depth camera, which comprises the following steps: acquiring a three-dimensional foot model; determining foot parameters according to the three-dimensional foot model; determining foot shape data according to the foot parameters; judging whether the foot shape is abnormal according to the foot shape data and determining the type of the foot shape; if the foot shape is abnormal, determining the severity degree of the arch and the degree of the footprint according to foot parameters; determining the degree of hindfoot eversion according to foot parameters; determining toe conditions according to foot parameters; establishing a virtual three-dimensional model according to the foot type data; acquiring external data and determining corresponding suggestion information by combining all the data; the advice information includes insole information. The insole type selection method solves the problem that deviation is easy to occur in insole type selection, and has the effect of giving a relatively accurate insole type selection suggestion.
Description
Technical Field
The invention relates to the technical field of insole matching, in particular to a depth camera-based insole matching method and system, an intelligent terminal and a storage medium.
Background
Currently, insoles are placed inside shoes to provide additional support to the arch of the foot and provide greater comfort to the wearer.
Currently, when the insole is selected, if the foot of the user belongs to a normal foot shape, the user can select a common normal insole; if the foot shape is special, an experienced doctor is needed to observe the foot, the foot is evaluated according to the observation result, and the insole type selection suggestion is given; the foot can also be scanned by infrared rays so as to obtain foot shape data, and a doctor gives insole type selection suggestions according to the foot shape data.
The above prior art solutions have the following drawbacks: because the judgment is carried out through the experience of doctors, the judgment result is subjective, the experience of each doctor is different, and the final judgment result is also different, so that the type selection of the insole has deviation; the infrared scanning speed is low, if the feet move in the scanning process, foot shape data errors are easily caused, misguidance is formed for doctors, and deviation exists in insole type selection; moreover, only the foot shape data is provided, the physician still needs to give insole type selection suggestions through self experience and the data, and the actually needed insole can deviate from the insole suggested by the physician, so that repeated attempts are needed to finally determine the insole type.
Disclosure of Invention
The invention aims to provide a depth camera-based insole matching method which has the characteristic of giving more accurate insole type selection suggestions.
The above object of the present invention is achieved by the following technical solutions:
a depth camera-based insole matching method comprises the following steps:
acquiring a three-dimensional foot model;
determining foot parameters according to the three-dimensional foot model;
determining foot shape data according to the foot parameters;
judging whether the foot shape is abnormal according to the foot shape data and determining the type of the foot shape;
if the foot shape is abnormal, determining the severity degree of the arch and the degree of the footprint according to foot parameters;
determining the degree of hindfoot eversion according to foot parameters;
determining toe conditions according to foot parameters;
establishing a virtual three-dimensional model according to the foot type data;
acquiring external data and determining corresponding suggestion information by combining all the data;
the advice information includes insole information.
By adopting the technical scheme, the three-dimensional foot model is obtained firstly, so that foot parameters can be determined according to the three-dimensional foot model, after the foot parameters are determined, foot type data can be determined according to the foot type data, the foot shape type can be determined according to the foot type data, if the foot shape type is abnormal foot shape, the severity degree of the arch of foot and the degree of foot print can be confirmed, meanwhile, the eversion degree of the back foot and the toe condition can be determined according to the foot parameters, so that the foot condition can be known in multiple dimensions, a virtual three-dimensional model can be established according to the foot type data, and suggestion information can be determined by combining external data and all the data, a doctor can comprehensively determine the insole through the virtual three-dimensional model, all the data and the suggestion information, and the doctor can judge and then select the insole or directly select the insole according to the suggestion information due to the information being given, so that the final insole shape selection suggestion conforms to the actual foot shape.
The present invention in a preferred example may be further configured to: the specific method for determining the foot shape data according to the foot parameters comprises the following steps:
acquiring arch height data in foot parameters;
acquiring arch length data in foot parameters;
determining the arch height ratio according to the arch height ratio = arch height/arch length;
and taking the arch height ratio value as foot type data.
By adopting the technical scheme, if the ratio of the arch height ratio to the arch length is larger, the arch is more bent, and if the ratio of the arch height ratio to the arch length is smaller, the arch is flatter, so that the arch height ratio value is equal to foot type data, and the foot shape types can be conveniently distinguished according to the values in the later period.
The present invention in a preferred example may be further configured to: the specific method for judging whether the foot shape is abnormal or not according to the foot shape data and determining the foot shape type comprises the following steps:
acquiring an abnormal foot shape threshold upper limit and an abnormal foot shape threshold lower limit;
judging whether the foot shape data is positioned between the upper limit of the abnormal foot shape threshold value and the lower limit of the abnormal foot shape threshold value;
if the foot shape is between the upper limit of the abnormal foot shape threshold value and the lower limit of the abnormal foot shape threshold value, the foot shape is a normal foot shape, and the foot shape type is a normal foot;
if the abnormal foot shape is not between the upper limit of the abnormal foot shape threshold value and the lower limit of the abnormal foot shape threshold value, the abnormal foot shape is determined;
if the upper limit of the abnormal foot shape threshold value is larger than the upper limit of the abnormal foot shape threshold value, the foot shape type is a high arch foot;
if the lower limit is less than the lower limit of the abnormal foot shape threshold value, the foot shape type is flat foot.
By adopting the technical scheme, when the foot shape data is between the upper limit and the lower limit, the foot shape data is in the normal range, the foot shape is normal, if the foot shape data is larger than the upper limit, the foot is high-arch foot, if the foot shape data is smaller than the lower limit, the foot shape data is flat foot, and the foot shape types are distinguished through the data, so that the finally determined foot shape is accurate.
The present invention in a preferred example may be further configured to: the specific method for determining the severity of the arch and the degree of the footprint according to the foot parameters comprises the following steps:
acquiring a middle foot footprint area in foot parameters;
acquiring a full-foot footprint area in foot parameters;
determining an arch index according to the arch index = mid-foot footprint area/full-foot footprint area;
acquiring grading information of the severity of the arch of the flat foot and grading information of the severity of the arch of the high arch foot;
acquiring the grading information of the footprints;
comparing the arch index with the grading information of the severity of the arch of the flat foot, the grading information of the severity of the arch of the high arch foot and the grading information of the footprint;
and determining the severity degree of the arch and the degree of the footprint according to the interval in which the arch index falls.
By adopting the technical scheme, when the foot shape type is flat foot or high arch foot, the severity and the footprint degree of the foot arch are determined according to the interval in which the foot arch index falls, so that the foot shape types with different foot arch indexes are further distinguished, the classification is more detailed, and the accuracy of later-stage insole type selection is improved.
The present invention in a preferred example may be further configured to: the specific method for determining the degree of hindfoot eversion according to foot parameters comprises the following steps:
determining the VI value according to VI = [ (1/2 AB-AC)/AB ] x 100;
acquiring hindpaw ectropion grading information;
comparing the VI value with the hindfoot valgus grading information;
determining the degree of hind paw eversion according to the interval in which the VI value falls;
a is the lateral malleolus position point, B is the medial malleolus position point, AB is the distance between the medial malleolus position point and the lateral malleolus position point, C is the intersection point of the second metatarsal head to the heel intermediate line and the AB line, and AC is the distance between the lateral malleolus position point and the intersection point.
By adopting the technical scheme, after the VI value is obtained, the foot eversion degree is determined according to the classification information of the interval in which the VI value falls, so that the eversion condition is more detailed on the basis of determining the foot eversion on the basis, and the accuracy of later-stage insole type selection is improved.
The present invention in a preferred example may be further configured to: the specific method for determining the toe condition according to the foot parameters comprises the following steps:
acquiring the maximum value of the inclination angle;
obtaining a toe camber angle in foot parameters;
if the toe out angle is greater than or equal to the maximum toe angle, the toe condition is defined as hallux valgus.
By adopting the technical scheme, when the camber angle of the hallux is larger than the maximum value, the hallux valgus is indicated, so that the condition of the toes is obtained, and the reference data in the later-stage insole model selection process is more diversified by obtaining the condition of the toes, so that the accuracy of later-stage insole model selection is improved.
The present invention in a preferred example may be further configured to: the specific method for determining the corresponding recommendation information comprises the following steps:
substituting external data and all the data into a preset connection node relation;
generating a next node according to the previous node information and substituting the nodes in sequence;
if the next node has no requirement on the data, the node is directly skipped over to enter the next node of the node;
when the final node is reached, outputting suggestion information according to the data of each node;
the insole information is final node data.
By adopting the technical scheme, after data is recorded in the previous node, data is recorded in the next node, so that different paths are selected according to different nodes, the final node is determined, and when the node has no data requirement, the node is skipped, and the final insole information is determined quickly and accurately.
The invention also aims to provide an insole matching system which has the characteristic of giving more accurate insole type selection suggestions.
The second aim of the invention is realized by the following technical scheme:
a depth camera based insole fitting system comprising:
the three-dimensional information acquisition unit is used for acquiring a three-dimensional foot model;
the foot parameter acquisition unit is used for determining foot parameters according to the three-dimensional foot model;
a foot type data acquisition unit; for determining foot shape data from the foot parameters;
a foot shape type determination unit; the device is used for judging whether the foot shape is abnormal according to the foot shape data and determining the type of the foot shape;
the arch and footprint determining unit is used for determining the severity of the arch and the degree of the footprint according to foot parameters;
the hindfoot valgus degree determining unit is used for determining the hindfoot valgus degree according to the foot parameters;
the toe condition determining unit is used for determining the toe condition according to the foot parameters;
a three-dimensional model establishing unit for establishing a virtual three-dimensional model according to the foot type data;
and the suggestion information generation unit is used for acquiring external data and determining corresponding suggestion information by combining all the data.
By adopting the technical scheme, the three-dimensional information acquisition unit acquires a three-dimensional foot model firstly, so that the foot parameter acquisition unit can determine foot parameters according to the three-dimensional foot model, after the foot parameters are determined, the foot type data acquisition unit determines foot type data according to the foot parameters, the foot type determination unit can determine the foot type according to the foot type data, if the foot type is abnormal foot shape, the arch and footprint determination unit confirms the severity of the arch and the footprint, meanwhile, the hindfoot eversion degree determination unit and the toe condition determination unit can also determine the hindfoot eversion degree and the toe condition according to the foot parameters, so that the foot condition is known in multiple dimensions, the three-dimensional model establishment unit establishes a virtual three-dimensional model according to the foot type data, and the suggestion information generation unit determines suggestion information by combining external data and all the data, the doctor can comprehensively determine the insole through the virtual three-dimensional model, all the data and the suggestion information, and the doctor can judge and then select the insole or directly select the insole according to the suggestion information because the insole information is given, so that the final insole type selection suggestion conforms to the actual foot type.
The invention aims to provide the intelligent terminal which has the characteristic of giving more accurate shoe pad type selection suggestions.
The third object of the invention is realized by the following technical scheme:
an intelligent terminal comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and executes the insole matching method.
By adopting the technical scheme, the three-dimensional foot model is obtained firstly, so that foot parameters can be determined according to the three-dimensional foot model, after the foot parameters are determined, foot type data can be determined according to the foot type data, the foot shape type can be determined according to the foot type data, if the foot shape type is abnormal foot shape, the severity degree of the arch of foot and the degree of foot print can be confirmed, meanwhile, the eversion degree of the back foot and the toe condition can be determined according to the foot parameters, so that the foot condition can be known in multiple dimensions, a virtual three-dimensional model can be established according to the foot type data, and suggestion information can be determined by combining external data and all the data, a doctor can comprehensively determine the insole through the virtual three-dimensional model, all the data and the suggestion information, and the doctor can judge and then select the insole or directly select the insole according to the suggestion information due to the information being given, so that the final insole shape selection suggestion conforms to the actual foot shape.
The fourth purpose of the invention is to provide a computer storage medium which can store corresponding programs and has the characteristic of being convenient for realizing giving more accurate insole type selection suggestions.
The fourth object of the invention is realized by the following technical scheme:
a computer readable storage medium storing a computer program that can be loaded by a processor and executed to perform any of the above methods for insole fitting.
By adopting the technical scheme, the three-dimensional foot model is obtained firstly, so that foot parameters can be determined according to the three-dimensional foot model, after the foot parameters are determined, foot type data can be determined according to the foot type data, the foot shape type can be determined according to the foot type data, if the foot shape type is abnormal foot shape, the severity degree of the arch of foot and the degree of foot print can be confirmed, meanwhile, the eversion degree of the back foot and the toe condition can be determined according to the foot parameters, so that the foot condition can be known in multiple dimensions, a virtual three-dimensional model can be established according to the foot type data, and suggestion information can be determined by combining external data and all the data, a doctor can comprehensively determine the insole through the virtual three-dimensional model, all the data and the suggestion information, and the doctor can judge and then select the insole or directly select the insole according to the suggestion information due to the information being given, so that the final insole shape selection suggestion conforms to the actual foot shape.
In summary, the invention includes at least one of the following beneficial technical effects:
1. determining foot parameters through a three-dimensional foot model, then determining foot type data, arch severity, footprint degree, hindfoot eversion degree and toe condition according to the foot parameters, and providing suggestion information by combining external data and all the data, so that more accurate suggestions are given to doctors, and the doctors can directly make type selection suggestions of insoles according to the suggestions or combine the suggestions, so that the finally determined insoles conform to actual feet;
2. the severity degree and the footprint degree of the arch are determined according to the arch index, and the hindfoot eversion degree is determined according to the VI value, so that the classification of the foot is more detailed, and the matched insole can be more accurately determined;
3. the final insole information is determined through the relation of the connection nodes, and if the next node has no requirement, the node is skipped over to enter the next node, so that the final node is determined more quickly, the substitution of meaningless data is removed, and the processing speed is increased.
Drawings
FIG. 1 is a block flow diagram of one embodiment of the present invention.
FIG. 2 is a schematic view of a footprint area of one embodiment of the present invention.
FIG. 3 is a schematic diagram of a location point according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a connection node according to an embodiment of the present invention.
FIG. 5 is a system block diagram of one embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiments of the present invention will be described in further detail with reference to the drawings attached hereto.
The embodiment of the invention provides a depth camera-based insole matching method, and the main flow of the method is described as follows.
Referring to fig. 1, a three-dimensional model of a foot is acquired, and the three-dimensional model of the foot is acquired by a depth camera.
And determining foot parameters according to the three-dimensional foot model, and reading various parameters in the three-dimensional foot model to determine the foot parameters.
And determining foot shape data according to the foot parameters, and calculating the foot shape data according to the foot parameter information. The method comprises the steps of firstly obtaining arch height from foot parameters, then obtaining arch length from the foot parameters, and then determining an AHR value according to a company formula AHR (arch height ratio) = arch height/arch length, wherein the AHR value is foot type data.
Judging whether the foot shape is abnormal according to the foot shape data, determining the foot shape type, and firstly acquiring the upper limit of the threshold value of the abnormal foot shape and the lower limit of the threshold value of the abnormal foot shape. If the AHR value is less than or equal to the upper limit of the abnormal foot shape threshold value and greater than or equal to the lower limit of the abnormal foot shape threshold value, the current foot shape type is a normal foot, if the AHR value is not between the upper limit of the abnormal foot shape threshold value and the lower limit of the abnormal foot shape threshold value, the current foot shape type is an abnormal foot shape, if the AHR value is greater than the upper limit of the abnormal foot shape threshold value, the foot shape type is a high arch foot, and if the AHR value is less than the lower limit of the abnormal foot shape threshold value, the foot shape type is a flat foot.
If the foot shape type is a high arch foot, firstly acquiring a middle foot footprint area (B in fig. 2) and a full foot footprint area (A + B + C in fig. 2) in foot parameters, determining an arch index by a formula Arch Index (AI) = middle foot footprint area/full foot footprint area, and then acquiring grading information of the arch severity of the high arch foot: an AI value less than a mild rating threshold is defined as mild; if the AI value is between the zero value and the moderate grading threshold value, the AI value is defined as moderate; AI values between the zero value and the medium classification threshold, with a claw toe, are defined as severe. The arch severity of the high arch foot is determined based on which interval the arch index lies in, e.g., if the current foot's AI value falls within a medium interval, the arch severity of the high arch foot is medium. Also obtains the footprint grading information: if the AI value is greater than the vertex value, defining as outstanding; if the AI value is between the middle value and the top value, the filling is defined; the AI value is between the low-point value and the middle value, and the space is defined to be less; if the AI value is between the low-point value and the normal value, the AI value is defined as normal; the AI value is smaller than the normal value, and the space is defined to be larger; an AI value of abnormal value is defined as off. The degree of footprint is determined according to which interval the arch index lies in, e.g., if the current foot AI value is between a low point value and a normal value, the degree of footprint of the arch foot is normal.
If the foot shape type is flat foot, firstly acquiring a middle foot footprint area (B in fig. 2) and a full foot footprint area (A + B + C in fig. 2) in foot parameters, determining an arch index by a formula Arch Index (AI) = middle foot footprint area/full foot footprint area, and then acquiring the classification information of the arch severity of the flat foot: AI values less than a mild value are defined as mild; if the AI value is greater than the slight value and less than the medium value, the AI value is defined as medium; an AI value greater than the median value is defined as severe. The severity of the arch of the flat foot is determined according to which interval the arch index is located, for example, if the current AI value of the foot is smaller than a slight value, the severity of the arch of the flat foot falls into a slight interval, and the severity of the arch of the flat foot is slight. Also obtains the footprint grading information: if the AI value is greater than the vertex value, defining as outstanding; if the AI value is between the middle value and the top value, the filling is defined; the AI value is between the low-point value and the middle value, and the space is defined to be less; if the AI value is between the low-point value and the normal value, the AI value is defined as normal; the AI value is smaller than the normal value, and the space is defined to be larger; an AI value of abnormal value is defined as off. The degree of the footprint is determined according to which section the arch index is located in, and the degree of the footprint is determined according to which section the arch index is located in, for example, if the AI value of the current foot is an abnormal value, the degree of the footprint of the flat foot is broken.
Determining the degree of hindfoot eversion according to foot parameters, determining a lateral malleolus position point (point A in fig. 3), a medial malleolus position point (point B in fig. 3), and an intersection point of a second metatarsal head to a heel middle line and an AB connecting line (point C in fig. 3) according to the foot parameters, thereby determining a distance AB between the point A and the point B and a distance AC between the point A and the point C, and determining a VI value by a formula VI = [ (1/2 AB-AC)/AB ] x 100. And then acquiring hindpaw ectropion grading information: if the VI value is larger than the extreme valgus value, the severe valgus is defined; VI value is between the extreme valgus value and the obvious valgus value, and then is defined as obvious valgus; a VI value between the pronounced valgus value and the slight valgus value is defined as slight valgus; a VI value between the slight valgus value and the base foot value is defined as vertical; a VI value is between the base foot value and the slight inversion value, and then the slight inversion is defined; VI values between the slightly inverted value and the obvious inverted value are defined as obvious inversion; and if the VI value is less than the inversion extreme value, defining the serious inversion. The degree of hindfoot eversion is determined by which interval the VI value lies, e.g., if the VI value of the current foot lies between the base foot value and the slight inversion value, then the foot is slightly inverted.
And determining the toe condition according to the foot parameters, acquiring the maximum value of the inclination angle, then acquiring the toe extroversion angle in the foot parameters, and if the toe extroversion angle is larger than the maximum value of the inclination angle, defining the toe eversion, otherwise, the toe eversion is normal.
And establishing a virtual three-dimensional model according to the foot shape data, and directly observing the virtual three-dimensional model after the virtual three-dimensional model is output.
Referring to fig. 4, external data including, but not limited to, a pain level, a frequently worn footwear, a knee joint, and a pain position is acquired and combined with all the data to determine corresponding advice information, and the external data and all the data are substituted into a preset connection node relationship, and then a subsequent node is generated based on previous node information and substituted in order. When the next node has no requirement on the data, the node is directly skipped and the data of the next node of the node is substituted, and when the final node is reached, the data of each node is obtained, so that the suggestion information is output. For example, the preset connection node relationship is pain degree-commonly worn shoes-hind foot eversion-foot type-knee joint-pain position-insole, after the general is substituted in the pain degree node, the next commonly worn shoes node is generated to substitute data, after the sports shoes are substituted in the commonly worn shoes node, hind foot eversion node is generated, the VI values of the left foot and the right foot are substituted in the hind foot eversion node to generate foot type node, slight high arch foot is substituted in the foot type node to generate knee joint node, at the moment, the knee joint node has no requirement on the data, the pain position node is generated, at the moment, the pain position node has no requirement on the data, the final node is reached, the insole information is generated, the information of all the nodes is output, and the information of all the nodes can be visually seen.
Referring to fig. 5, the insole matching system based on the depth camera comprises a three-dimensional information acquisition unit, a foot parameter acquisition unit, a foot type data acquisition unit, a foot shape type determination unit, an arch and footprint determination unit, a hindfoot eversion degree determination unit, a toe condition determination unit, a three-dimensional model building unit and a suggestion information generation unit. The foot parameter acquisition unit is electrically connected with the three-dimensional information acquisition unit, receives the three-dimensional foot model acquired by the three-dimensional information acquisition unit, determines foot parameters according to the three-dimensional foot model and outputs the foot parameters. The foot type data acquisition unit is electrically connected with the foot parameter acquisition unit, and the foot type data acquisition unit determines and outputs foot type data according to the transmitted foot parameters. The foot shape type determining unit is electrically connected with the foot shape data acquiring unit, judges whether the foot shape is abnormal according to the foot shape data transmitted by the foot shape data acquiring unit and determines the foot shape type, the arch and footprint determining unit is electrically connected with the foot shape type determining unit, and determines the arch severity and the footprint degree of the abnormal foot shape according to foot parameters. The hindfoot eversion degree determining unit and the toe condition determining unit are electrically connected with the foot parameter acquiring unit, the hindfoot eversion degree determining unit determines the hindfoot eversion degree according to the foot parameters, and the toe condition determining unit determines the toe condition according to the foot parameters. The three-dimensional model establishing unit is electrically connected with the foot type data acquiring unit, and establishes a virtual three-dimensional model of the foot after the foot type data is acquired. The foot shape type determining unit, the arch and footprint determining unit, the hindfoot eversion degree determining unit and the toe condition determining unit are all electrically connected with the suggestion information generating unit, and the suggestion information generating unit generates corresponding suggestion information by acquiring data input by the outside and data input by the four units.
An intelligent terminal comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and executes the flow shown in figure 1.
A computer readable storage medium storing a computer program capable of being loaded by a processor and executing a process as shown in fig. 1. The computer-readable storage medium includes, for example: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Claims (10)
1. A shoe pad matching method based on a depth camera is characterized by comprising the following steps:
acquiring a three-dimensional foot model;
determining foot parameters according to the three-dimensional foot model;
determining foot shape data according to the foot parameters;
judging whether the foot shape is abnormal according to the foot shape data and determining the type of the foot shape;
if the foot shape is abnormal, determining the severity degree of the arch and the degree of the footprint according to foot parameters;
determining the degree of hindfoot eversion according to foot parameters;
determining toe conditions according to foot parameters;
establishing a virtual three-dimensional model according to the foot type data;
acquiring external data and determining corresponding suggestion information by combining all the data;
the advice information includes insole information.
2. The method of claim 1, wherein the specific method of determining foot shape data from foot parameters comprises:
acquiring arch height data in foot parameters;
acquiring arch length data in foot parameters;
determining the arch height ratio according to the arch height ratio = arch height/arch length;
and taking the arch height ratio value as foot type data.
3. The method for matching depth camera-based shoe insoles according to claim 1, wherein the specific method for determining whether the foot shape is abnormal according to the foot shape data and determining the type of the foot shape comprises:
acquiring an abnormal foot shape threshold upper limit and an abnormal foot shape threshold lower limit;
judging whether the foot shape data is positioned between the upper limit of the abnormal foot shape threshold value and the lower limit of the abnormal foot shape threshold value;
if the foot shape is between the upper limit of the abnormal foot shape threshold value and the lower limit of the abnormal foot shape threshold value, the foot shape is a normal foot shape, and the foot shape type is a normal foot;
if the abnormal foot shape is not between the upper limit of the abnormal foot shape threshold value and the lower limit of the abnormal foot shape threshold value, the abnormal foot shape is determined;
if the upper limit of the abnormal foot shape threshold value is larger than the upper limit of the abnormal foot shape threshold value, the foot shape type is a high arch foot;
if the lower limit is less than the lower limit of the abnormal foot shape threshold value, the foot shape type is flat foot.
4. The depth camera-based insole matching method according to claim 1, wherein the specific method for determining the degree of arch severity and the degree of footprint based on foot parameters comprises:
acquiring a middle foot footprint area in foot parameters;
acquiring a full-foot footprint area in foot parameters;
determining an arch index according to the arch index = mid-foot footprint area/full-foot footprint area;
acquiring grading information of the severity of the arch of the flat foot and grading information of the severity of the arch of the high arch foot;
acquiring the grading information of the footprints;
comparing the arch index with the grading information of the severity of the arch of the flat foot, the grading information of the severity of the arch of the high arch foot and the grading information of the footprint;
and determining the severity degree of the arch and the degree of the footprint according to the interval in which the arch index falls.
5. The method of claim 1, wherein the specific method of determining the degree of hindfoot eversion from foot parameters comprises:
determining the VI value according to VI = [ (1/2 AB-AC)/AB ] x 100;
acquiring hindpaw ectropion grading information;
comparing the VI value with the hindfoot valgus grading information;
determining the degree of hind paw eversion according to the interval in which the VI value falls;
a is the lateral malleolus position point, B is the medial malleolus position point, AB is the distance between the medial malleolus position point and the lateral malleolus position point, C is the intersection point of the second metatarsal head to the heel intermediate line and the AB line, and AC is the distance between the lateral malleolus position point and the intersection point.
6. The depth camera-based insole fitting method according to claim 1, wherein the specific method for determining toe condition according to foot parameters comprises:
acquiring the maximum value of the inclination angle;
obtaining a toe camber angle in foot parameters;
if the toe out angle is greater than or equal to the maximum toe angle, the toe condition is defined as hallux valgus.
7. The depth camera-based insole matching method according to claim 1, wherein the specific method for determining the corresponding advice information comprises:
substituting external data and all the data into a preset connection node relation;
generating a next node according to the previous node information and substituting the nodes in sequence;
if the next node has no requirement on the data, the node is directly skipped over to enter the next node of the node;
when the final node is reached, outputting suggestion information according to the data of each node;
the insole information is final node data.
8. An insole matching system based on a depth camera, comprising:
the three-dimensional information acquisition unit is used for acquiring a three-dimensional foot model;
the foot parameter acquisition unit is used for determining foot parameters according to the three-dimensional foot model;
a foot type data acquisition unit; for determining foot shape data from the foot parameters;
a foot shape type determination unit; the device is used for judging whether the foot shape is abnormal according to the foot shape data and determining the type of the foot shape;
the arch and footprint determining unit is used for determining the severity of the arch and the degree of the footprint according to foot parameters;
the hindfoot valgus degree determining unit is used for determining the hindfoot valgus degree according to the foot parameters;
the toe condition determining unit is used for determining the toe condition according to the foot parameters;
a three-dimensional model establishing unit for establishing a virtual three-dimensional model according to the foot type data;
and the suggestion information generation unit is used for acquiring external data and determining corresponding suggestion information by combining all the data.
9. An intelligent terminal, comprising a memory and a processor, the memory having stored thereon a computer program that can be loaded by the processor and that executes the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which can be loaded by a processor and which executes the method of any one of claims 1 to 7.
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