A body type determination method, apparatus, device and storage medium

Abstract

The application discloses a body type determination method, device and equipment and a storage medium, and comprises the following steps: obtaining monitoring information transmitted by a monitoring device, wherein the monitoring information comprises current sleeping posture information of a target object and air bag pressure information of an air bag in the monitoring device; determining a first corresponding relationship between the air bag position in the monitoring device and the object part of the target object according to the air bag pressure information; and determining the body type of the target object according to the first corresponding relationship and the current sleeping posture information. The above technical solution solves the problem that the size of the body part of the target object needs to be determined in advance to further determine the body type of the target object, and can directly determine the body type of the target object according to the monitoring information during the rest of the target object, thereby improving the efficiency of body type determination and ensuring the accuracy and convenience of body type determination.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent mattress, and in particular to a body type determination method, device, equipment and storage medium. BACKGROUND

[0002] Body type refers to the shape characteristics and body type of a human body, which can be classified according to the body shape characteristics of different characteristics. There are many methods and standards for body type classification.

[0003] At present, the existing body type classification and determination method often needs to measure the size of the key body part of the human body as a characteristic index, evaluate the characteristic index, and classify the body type according to the evaluation result of the characteristic index combined with the model. This body type classification method needs to measure the size of the body part of the target object in advance to realize the classification and determination of the body type, which is relatively complex in application. SUMMARY

[0004] The present application provides a body type classification method, device, equipment and storage medium, which solves the problem that the size of the body part of the target object needs to be determined in advance to further determine the body type of the target object, and can directly determine the body type of the target object according to the monitoring information of the target object during rest, improving the efficiency of body type determination and ensuring the accuracy and convenience of body type determination.

[0005] In a first aspect, the present application provides a body type determination method, comprising:

[0006] obtaining monitoring information transmitted by a monitoring device, wherein the monitoring information comprises current sleep posture information of a target object and air bag pressure information of an air bag in the monitoring device;

[0007] determining a first correspondence relationship between the air bag position in the monitoring device and the object part of the target object according to the air bag pressure information;

[0008] determining the body type of the target object according to the first correspondence relationship and the current sleep posture information.

[0009] In a second aspect, the present application provides a body type determination device, comprising:

[0010] a monitoring information acquisition module, configured to obtain monitoring information transmitted by a monitoring device, wherein the monitoring information comprises current sleep posture information of a target object and air bag pressure information of an air bag in the monitoring device;

[0011] a correspondence relationship determination module, configured to determine a first correspondence relationship between the air bag position in the monitoring device and the object part of the target object according to the air bag pressure information;

[0012] An object size determination module is configured to determine the size of the target object according to the first correspondence relationship and the current sleep position information.

[0013] In a third aspect, an electronic device is provided, and the electronic device comprises:

[0014] at least one processor; and

[0015] a memory in communication with the at least one processor; wherein

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the size determination method provided in the first aspect.

[0017] In a fourth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores computer instructions for enabling a processor to implement the size determination method provided in the first aspect when the processor executes the computer instructions.

[0018] The size determination method, device, equipment and storage medium provided in the embodiments of the present application can obtain monitoring information transmitted by a monitoring device, the monitoring information comprising current sleep position information of a target object and airbag pressure information of an airbag in the monitoring device, determine a first correspondence relationship between a position of the airbag in the monitoring device and an object part of the target object according to the airbag pressure information, and determine the size of the target object according to the first correspondence relationship and the current sleep position information. The above technical solution solves the problem that the size of the target object can be determined only after the size of the body part of the target object is determined, and can determine the size of the target object directly according to monitoring information during the rest of the target object, thereby improving the efficiency of size determination and ensuring the accuracy and convenience of size determination.

[0019] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort.

[0021] Figure 1is a flow chart of a body type determination method provided by an embodiment of the present application;

[0022] Figure 2 is a flow chart of a body type determination method provided by an embodiment of the present application;

[0023] Figure 3 is a structural schematic diagram of a body type determination device provided by an embodiment of the present application;

[0024] Figure 4 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor should fall within the protection scope of the present application.

[0026] It should be noted that the terms "first", "second" and "target" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment one

[0028] Figure 1 is a flow chart of a body type determination method provided by an embodiment of the present application, and the present embodiment can be applicable to the case of determining the body type of a target object according to the monitoring data of the target object during rest. The method can be executed by a body type determination device, which can be realized in the form of hardware and / or software.

[0029] As shown in Figure 1 , the method comprises:

[0030] S101, acquiring monitoring information transmitted by a monitoring device, the monitoring information comprising current sleeping posture information of a target object and airbag pressure information of an airbag in the monitoring device.

[0031] In this embodiment, the monitoring device can be understood as a device for data monitoring during the rest of the target object, which can be a smart mattress containing multiple airbags. The target object can be understood as the user of the smart mattress (monitoring device). The monitoring information can be understood as the information detected by the monitoring device, including the current sleeping posture information of the target object and the airbag pressure information of the airbags in the monitoring device. Among them, the current sleeping posture information can be understood as the posture of the target object resting on the smart mattress (monitoring device), which can include various postures such as lying flat and lying on the side. The airbag pressure information can be understood as the pressure value borne by each airbag position in the airbag of the mattress, which can include the pressure value of each airbag position when no one is on the mattress, and can also include the pressure value of each airbag position when someone is on the mattress.

[0032] Specifically, the monitoring device records the airbag pressure information in real time, and when the airbag pressure information produces a positive growth change in pressure and the change amount is greater than a certain preset threshold, it is determined that there is a target object on the mattress, wherein the preset threshold is a weight change value, and the species of the target object is determined according to the amount of change in the positive growth of the airbag pressure information, for example, when the positive growth change amount of the airbag pressure information of each airbag is greater than a kilogram, it can be determined that the target object is a human. When the target object is a human, the current sleeping posture of the target object is detected to determine the current sleeping posture information of the target object, wherein the airbag pressure information obtained by the monitoring device includes the airbag pressure value when no one is on the mattress and the airbag pressure value when someone is on the mattress. When a body type determination requirement is generated, a monitoring data calling request is generated, and the generated monitoring data calling request is sent to the monitoring device to obtain the current sleeping posture information of the target object and the airbag pressure information of the airbags returned by the monitoring device.

[0033] S102, according to the airbag pressure information, determine the first correspondence relationship between the airbag position in the monitoring device and the object part of the target object.

[0034] In this embodiment, the airbag position can be understood as the position in the mattress (monitoring device), which can be represented in the form of a number. The object part can be understood as the body part of the target object, and the first correspondence relationship can be understood as the correspondence relationship between the airbag position and the object part, for example, the correspondence relationship between the airbag with position number 1 and the shoulder of the target object.

[0035] Among them, the object part of the target object at least includes: shoulder, back, waist, hip and leg.

[0036] Specifically, the pressure change value of the air bag is determined according to the air bag pressure value when a person is on the mattress and the air bag pressure value when no person is on the mattress contained in the air bag pressure information, and the first corresponding relationship between the air bag position in the monitoring device and the object part of the target object is determined according to the air bag pressure change value and a preset corresponding relationship determination mode. The preset corresponding relationship determination mode can be an algorithm, a model, or a set threshold strategy, and the present embodiment is not limited in this regard.

[0037] For example, according to the air bag pressure information, the pressure change value corresponding to each air bag position is determined, and the object part of the target object corresponding to the air bag position is determined according to the air bag pressure change value of each position, for example, air bag 1 corresponds to the shoulder, air bag 2 corresponds to the waist, air bag 3 corresponds to the back, air bag 4 corresponds to the hips, and air bag 5 corresponds to the legs.

[0038] S103, determining the body type of the target object according to the first corresponding relationship and the current sleeping position information.

[0039] In the present embodiment, the body type of the target object can be understood as the body type of the target object, including inverted triangular type, rectangular type, apple type, pear type and hourglass type.

[0040] Specifically, according to the corresponding relationship between the air bag position of the monitoring device and the object part of the target object in the first corresponding relationship, the pressure change value of the air bag corresponding to the object part of the target object is determined, and the body type of the target object is determined according to the pressure change value of the object part and the current sleeping position information of the target object in combination with a preset body type determination mode. The preset body type determination mode can be an algorithm, a model, or a set threshold strategy, and the present embodiment is not limited in this regard.

[0041] For example, according to the corresponding relationship between the air bag position of the monitoring device and the object part of the target object, the pressure change value corresponding to each object part is determined, for example, the shoulder corresponds to the pressure change value a, the back corresponds to the pressure change value b, the waist corresponds to the pressure change value c, the hips correspond to the pressure change value d, and the legs correspond to the pressure change value e. When the current sleeping position of the target object is lying flat, the body type of the target object is determined according to the five pressure change values a, b, c, d, e and the object parts corresponding thereto, and the current sleeping position of lying flat.

[0042] In the embodiment, the monitoring information transmitted by the monitoring device is acquired, the monitoring information includes current sleeping posture information of the target object and air bag pressure information of the air bags in the monitoring device; the first correspondence relationship between the air bag positions in the monitoring device and the object parts of the target object is determined according to the air bag pressure information; and the body shape of the target object is determined according to the first correspondence relationship and the current sleeping posture information. The above technical solution solves the problem that the size of the body part of the target object needs to be determined in advance to further determine the body shape of the target object, and can directly determine the body shape of the target object according to the monitoring information during the rest of the target object, thereby improving the efficiency of body shape determination and ensuring the accuracy and convenience of body shape determination.

[0043] Embodiment two

[0044] Figure 2 is a flowchart of a body shape determination method provided by the second embodiment of the application, and the embodiment is a further optimization of any of the above embodiments, and can be applied to the case of determining the body shape of the target object according to the monitoring data during the rest of the target object. The method can be executed by a body shape determination device, which can be realized in the form of hardware and / or software.

[0045] As shown in Figure 2 , the method comprises:

[0046] S201, acquiring monitoring information transmitted by a monitoring device, the monitoring information including current sleeping posture information of a target object and air bag pressure information of air bags in the monitoring device.

[0047] S202, determining a first pressure change value corresponding to each air bag position in the monitoring device according to an initial pressure value and a current pressure value corresponding to each air bag position.

[0048] In the embodiment, the air bag pressure information of the air bags in the monitoring device includes an initial pressure value and a current pressure value corresponding to each air bag position. The initial pressure value can be understood as the pressure value of each air bag position when there is no target object on the intelligent mattress (monitoring device) and no one is on the intelligent mattress (monitoring device). The current pressure value can be understood as the pressure value of each air bag position when the target object is on the intelligent mattress (monitoring device). The first pressure change value can be understood as the difference between the initial pressure value and the current pressure value at the same air bag position.

[0049] Specifically, the difference between the initial pressure value and the current pressure value corresponding to each air bag position in the monitoring device is calculated, and the difference between the initial pressure value and the current pressure value of each air bag position is determined as the first pressure change value corresponding to the air bag position.

[0050] S203, determining a first correspondence relationship between the air bag positions in the monitoring device and the object parts of the target object according to the first pressure change value.

[0051] In this embodiment, the first pressure change value corresponding to each air bag position is input into the model for body part recognition, and a first correspondence relationship between the air bag position and the object part of the target object output by the model after calculation is obtained.

[0052] For example, the first pressure change value of air bag 1 is a, the first pressure change value of air bag 2 is b, the first pressure change value of air bag 3 is c, the first pressure change value of air bag 4 is d, and the first pressure change value of air bag 5 is e, which are input into the model for body part recognition, and the result output by the model is that air bag 1 corresponds to the shoulder, air bag 2 corresponds to the back, air bag 3 corresponds to the waist, air bag 4 corresponds to the hips, and air bag 5 corresponds to the legs.

[0053] S204, according to the first correspondence relationship and the first pressure change value corresponding to each air bag position in the monitoring device, determine the second pressure change value corresponding to each object part of the target object.

[0054] In this embodiment, the second pressure change value can be understood as the pressure change value corresponding to the object part of the target object, which has the same numerical value as the first pressure change value.

[0055] Specifically, according to the first correspondence relationship between the air bag position and the object part, and the first pressure change value corresponding to the air bag position, the second pressure change value corresponding to the object part of the target object is determined.

[0056] For example, air bag 1 corresponds to the shoulder, and the first pressure change value of air bag 1 is a, so the second pressure change value corresponding to the shoulder can also be determined as a.

[0057] S205, determine the body type of the target object according to the second pressure change value and the current sleeping posture information.

[0058] In this embodiment, the second pressure change value corresponding to each object part is input into the model for body type classification and determination, and the body type of the target object output by the model after calculation is obtained.

[0059] For example, the second pressure change value of the shoulder is a, the second pressure change value of the back is b, the second pressure change value of the waist is c, the second pressure change value of the hips is d, and the second pressure change value of the legs is e, which are input into the model for body type classification and determination, and the result output by the model is that the body type of the target object is apple type.

[0060] In the embodiment, the monitoring information transmitted by the monitoring device is acquired, the monitoring information including current sleeping position information of the target object and air bag pressure information of the air bags in the monitoring device; a first pressure change value corresponding to each air bag position in the monitoring device is determined according to an initial pressure value and a current pressure value corresponding to each air bag position; a first corresponding relationship between the air bag positions in the monitoring device and the object parts of the target object is determined according to the first pressure change value; a second pressure change value corresponding to each object part of the target object is determined according to the first corresponding relationship and the first pressure change value corresponding to each air bag position in the monitoring device; and the body type of the target object is determined according to the second pressure change value and the current sleeping position information. The above technical solution solves the problem that the size of the body part of the target object needs to be determined in advance to further determine the body type of the target object, and can directly determine the body type of the target object according to the monitoring information during the rest of the target object, thereby improving the efficiency of body type determination and ensuring the accuracy and convenience of body type determination.

[0061] As a first optional embodiment of the embodiment, the first optional embodiment further optimizes and adds a determination step of determining the first corresponding relationship between the air bag positions in the monitoring device and the object parts of the target object according to the first pressure change value on the basis of the above embodiment, including: inputting the first pressure change value into a pre-trained complete body part recognition model to obtain a recognition result output by the body part recognition model, and the recognition result is the first corresponding relationship between the air bag positions in the monitoring device and the object parts of the target object.

[0062] In the embodiment, the first pressure change value is inputted as an input value of the model into a pre-trained complete body part recognition model to obtain a recognition result output by the body part recognition model, and the recognition result is the first corresponding relationship between the air bag positions in the monitoring device and the object parts of the target object.

[0063] For example, the first pressure change value of the air bag 1 is a, the first pressure change value of the air bag 2 is b, the first pressure change value of the air bag 3 is c, the first pressure change value of the air bag 4 is d, and the first pressure change value of the air bag 5 is e, which are inputted into the model for body part recognition, and the result output by the model is that the air bag 1 corresponds to the shoulder, the air bag 2 corresponds to the back, the air bag 3 corresponds to the waist, the air bag 4 corresponds to the hips, and the air bag 5 corresponds to the legs.

[0064] The training step of the body part recognition model is as follows: a body part recognition model is constructed; a large amount of sample data of the body part recognition model is obtained, wherein the sample data includes a pressure change value of an initial pressure value and a current pressure value of an air bag, air bag position information, object part information, and a corresponding relationship among each pressure change value, air bag position information and object part information; based on the large amount of sample data, the body part recognition model is back propagated according to a set loss function to obtain the body part recognition model for the next iteration, and the next iteration is entered until an iteration end condition is met, so as to realize the training of the body part recognition model.

[0065] As a second optional embodiment of the embodiment, on the basis of the above embodiment, the second optional embodiment further optimizes and adds a determination step of determining the body type of the target object according to the second pressure change value and the current sleep position information, which comprises: inputting the second pressure change value and the current sleep position information into a pre-trained complete body type detection classification model to obtain a classification result output by the body type detection classification model, and determining the classification result as the body type of the target object.

[0066] In the embodiment, the second pressure change value and the current sleep position information are input into the pre-trained complete body type detection classification model as input values of the model, a classification result output by the body type detection classification model is obtained, and the classification result is determined as the body type of the target object.

[0067] For example, the second pressure change value of the shoulder is a, the second pressure change value of the back is b, the second pressure change value of the waist is c, the second pressure change value of the hip is d, the second pressure change value of the leg is e, and the current sleep position of the target object is lying, which are input into the model for body type classification and determination, the classification result output by the model is that the body type of the target object is apple type, and the apple type is determined as the body type of the target object.

[0068] The training step of the body type detection classification model is as follows: a body type detection classification model is constructed; a large amount of sample data of the body type detection classification model is obtained, wherein the sample data includes sleep position information of a target object, air bag pressure change values corresponding to object part information, and a body type of the target object; based on the sample data, the body type detection classification model is back propagated according to a set loss function to obtain the body type detection classification model for the next iteration, and the next iteration is entered until an iteration end condition is met, so as to realize the training of the body type detection classification model.

[0069] As a third optional embodiment of the embodiment, on the basis of the above embodiment, the third optional embodiment further optimizes and adds that the first pressure change value corresponding to the air bag position and the second pressure change value corresponding to the object part are the same air bag pressure change value, and the method further comprises:

[0070] a1) According to the first corresponding relationship, the air bag pressure change value, the current sleeping position information and the body type of the target object, a second corresponding relationship between the air bag position, the object part, the air bag pressure change value, the current sleeping position information and the body type is formed.

[0071] In this embodiment, according to the first corresponding relationship between the air bag position and the object part, the corresponding relationship between the air bag position and the object part and the air bag pressure change value, and the corresponding relationship between the air bag pressure change value and the current sleeping position information and the body type of the target object, a second corresponding relationship between the air bag position, the object part, the air bag pressure change value, the current sleeping position information and the body type is formed.

[0072] For example, the second corresponding relationship can be expressed as "air bag 1-shoulder-a-flat lying-apple type".

[0073] b1) According to the second corresponding relationship, a body type association information table is formed, and the body type association information table is stored in a preset database.

[0074] In this embodiment, the body type association information table can be understood as an association information table between the air bag position, the object part, the air bag pressure change value, the current sleeping position information and the body type, which is embodied in the form of a table.

[0075] Specifically, according to the second corresponding relationship, an association information table between the air bag position, the object part, the air bag pressure change value, the current sleeping position information and the body type is formed, and the association information table is stored in a preset database, so as to call the data of the body type association information table from the database when a specific demand occurs.

[0076] For example, the body type association information table is shown in the following table:

[0077] Airbag position Object part Airbag pressure change value Current sleeping position information Body type Airbag 1 Shoulder a Lying down Apple type

[0078] The body type determination method provided by the optional embodiment can enrich the user portrait by storing the body type of the target object and the corresponding other information into the database, so as to call the data of the body type association information table from the database when a specific demand occurs, and in the application scenarios of intelligent adjustment and mattress recommendation, a more refined adjustment scheme and recommendation scheme can be provided in combination with the user body type, thereby improving the user experience.

[0079] Embodiment three

[0080] Figure 3 is a structural schematic diagram of a body type determination device provided by the embodiment three of the present application. As shown in the figure, Figure 3 the device comprises:

[0081] The monitoring information acquisition module 31 is configured to acquire monitoring information transmitted by the monitoring device, wherein the monitoring information comprises current sleeping position information of the target object and air bag pressure information of air bags in the monitoring device;

[0082] The corresponding relationship determination module 32 is configured to determine a first corresponding relationship between air bag positions in the monitoring device and object parts of the target object according to the air bag pressure information.

[0083] The object body type determination module 33 is configured to determine a body type of the target object according to the first corresponding relationship and the current sleeping position information.

[0084] The body type determination device solves the problem that the size of the target object part needs to be determined in advance to further determine the body type of the target object, and can directly determine the body type of the target object according to the monitoring information during the rest of the target object, thereby improving the efficiency of the body type determination and ensuring the accuracy and convenience of the body type determination.

[0085] Optionally, the air bag pressure information comprises an initial pressure value and a current pressure value corresponding to each air bag position, and the corresponding relationship determination module 32 comprises:

[0086] The first difference value determination unit is configured to determine a first pressure change value corresponding to each air bag position in the monitoring device according to the initial pressure value and the current pressure value corresponding to each air bag position.

[0087] The first relationship determination unit is configured to determine a first corresponding relationship between air bag positions in the monitoring device and object parts of the target object according to the first pressure change value.

[0088] Optionally, the first relationship determination unit is specifically configured to:

[0089] input the first pressure change value into a pre-trained complete body part recognition model to obtain a recognition result output by the body part recognition model, wherein the recognition result is the first corresponding relationship between the air bag positions in the monitoring device and the object parts of the target object.

[0090] Optionally, the object body type determination module 33 comprises:

[0091] The second difference value determination unit is configured to determine a second pressure change value corresponding to each object part of the target object according to the first corresponding relationship and the first pressure change value corresponding to each air bag position in the monitoring device.

[0092] The body type determination unit is configured to determine a body type of the target object according to the second pressure change value and the current sleeping position information.

[0093] Optionally, the body type determination unit is specifically used for:

[0094] inputting the second pressure change value and the current sleep position information into a pre-trained complete body type detection classification model to obtain a classification result output by the body type detection classification model, and determining the classification result as the body type of the target object.

[0095] Optionally, the first pressure change value corresponding to the airbag position and the second pressure change value corresponding to the object part are the same airbag pressure change value, and the object body type determination module 33 is further used for:

[0096] forming a second correspondence relationship between the airbag position, the object part, the airbag pressure change value, the current sleep position information, and the body type according to the first correspondence relationship, the airbag pressure change value, the current sleep position information, and the body type of the target object.

[0097] forming a body type association information table according to the second correspondence relationship, and storing the body type association information table into a pre-set database.

[0098] Optionally, the object part of the target object at least includes shoulders, back, waist, hips, and legs.

[0099] The body type determination device provided in the embodiments of the present application can execute the body type determination method provided in any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0100] Embodiment Four

[0101] Figure 4 A structural schematic diagram of an electronic device 40 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0102] As Figure 4As shown, the electronic device 40 includes at least one processor 41, and a memory, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., connected to the at least one processor 41 in communication. The memory stores computer programs executable by the at least one processor 41, and the processor 41 can perform various appropriate actions and processes according to the computer programs stored in the read-only memory (ROM) 42 or loaded from the storage unit 48 into the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0103] Various components in the electronic device 40 are connected to the I / O interface 45, including an input unit 46, such as a keyboard, a mouse, etc., an output unit 47, such as various types of displays, a speaker, etc., a storage unit 48, such as a magnetic disk, an optical disk, etc., and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0104] The processor 41 can be various general and / or special-purpose processing components having processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 performs various methods and processes described above, such as the body type determination method.

[0105] In some embodiments, the body type determination method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the body type determination method described above can be performed. Alternatively, in other embodiments, the processor 41 can be configured to perform the body type determination method by any other appropriate means, such as by means of firmware.

[0106] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a load programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0107] Computer programs used to implement the processes of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program

[0108] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store computer programs for use by or in connection with an instruction execution system, apparatus, or device. Computer-readable storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, 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), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0109] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0110] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0111] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0112] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in sequence, or executed in a different order, as long as the desired results of the present disclosure are achieved, and the present disclosure is not limited herein.

[0113] The specific embodiments described above are not intended to be limiting, and persons skilled in the art will appreciate that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and principles of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above, but only by the scope of the appended claims.

Claims

1. A method for determining body shape, characterized in that, include: Acquire monitoring information transmitted by the monitoring device, the monitoring information including the current sleeping posture information of the target object and the airbag pressure information of the airbag in the monitoring device; Based on the airbag pressure information, a first correspondence is determined between the airbag position in the monitoring device and the object part of the target object, wherein the object part includes at least the shoulder, back, waist, buttocks and legs; Based on the first correspondence and the current sleeping posture information, the body shape of the target object is determined; The airbag pressure information includes the initial pressure value and the current pressure value corresponding to each airbag location. Accordingly, determining the first correspondence between the airbag locations in the monitoring device and the object parts of the target object based on the airbag pressure values ​​includes: Based on the initial pressure value and the current pressure value corresponding to each airbag position, determine the first pressure change value corresponding to each airbag position in the monitoring device; Based on the first pressure change value, a first correspondence is determined between the position of the airbag in the monitoring device and the object part of the target object; The step of determining the body shape of the target object based on the first correspondence and the current sleeping posture information includes: Based on the first correspondence and the first pressure change value corresponding to each airbag position in the monitoring device, the second pressure change value corresponding to each part of the target object is determined; The second pressure change value and the current sleeping posture information are input into a pre-trained body shape detection and classification model to obtain the classification result output by the body shape detection and classification model, and the classification result is determined as the body shape of the target object.

2. The method according to claim 1, characterized in that, Determining the first correspondence between the position of the airbag in the monitoring device and the object part of the target object based on the first pressure change value includes: The first pressure change value is input into a pre-trained body part recognition model to obtain the recognition result output by the body part recognition model. The recognition result is the first correspondence between the airbag position in the monitoring device and the object part of the target object.

3. The method according to claim 1, characterized in that, The method further includes the following: The first pressure change value corresponding to the airbag location and the second pressure change value corresponding to the object location are the same airbag pressure change value. Based on the first correspondence, the airbag pressure change value, the current sleeping posture information, and the body shape of the target object, a second correspondence is formed between the airbag location, the object part, the airbag pressure change value, the current sleeping posture information, and the body shape. A body type association information table is formed based on the second correspondence, and the body type association information table is stored in a preset database.

4. A body shape determination device, characterized in that, include: The monitoring information acquisition module is used to acquire the monitoring information transmitted by the monitoring device, including the current sleeping posture information of the target object and the airbag pressure information of the airbag in the monitoring device. The correspondence determination module is used to determine a first correspondence between the position of the airbag in the monitoring device and the object part of the target object based on the airbag pressure information, wherein the object part includes at least the shoulder, back, waist, buttocks and legs; The object body shape determination module is used to determine the body shape of the target object based on the first correspondence and the current sleeping posture information; The airbag pressure information includes the initial pressure value and the current pressure value corresponding to each airbag position. The correspondence determination module includes: The first difference determination unit is used to determine the first pressure change value corresponding to each airbag position in the monitoring device based on the initial pressure value and the current pressure value corresponding to each airbag position. The first relationship determination unit is used to determine a first correspondence between the position of the airbag in the monitoring device and the object part of the target object based on the first pressure change value; The object size determination module includes: The second difference determination unit is used to determine the second pressure change value corresponding to each part of the target object based on the first correspondence and the first pressure change value corresponding to each airbag position in the monitoring device. The body shape determination unit is used to input the second pressure change value and the current sleeping posture information into a pre-trained body shape detection and classification model, obtain the classification result output by the body shape detection and classification model, and determine the classification result as the body shape of the target object.

5. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform a body shape determination method according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute a body shape determination method according to any one of claims 1-3.

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