CN108563331A - Act matching result determining device, method, readable storage medium storing program for executing and interactive device - Google Patents

Abstract

Present disclose provides action matching result determining device, method, computer readable storage medium and the interactive devices in a kind of human-computer interaction, wherein the action matching result determining device in human-computer interaction includes：Interactive module acquires the action message of people for showing instruction image on the display unit；Grading module, for action message and the template operation to prestore to be obtained gross score every setting time；And execution module, matching result corresponding with gross score is shown on the display unit for controlling.

Description

Action matching result determination device, method, readable storage medium and interaction device

technical field

The present disclosure relates to the field of artificial intelligence, in particular, to a device for determining action matching results in human-computer interaction, a method for determining action matching results in human-computer interaction, a computer-readable storage medium, and a human-computer interaction device.

Background technique

The description of the background technology in the present disclosure belongs to the relevant technology related to the present disclosure, and is only used for illustration and to facilitate the understanding of the content of the present disclosure. prior art on the filing date.

In recent years, motion capture technology has become a key technology in the research of human motion posture, playing an increasingly important role. People realize that it is very necessary to realize the interactive function between human motion and information equipment by recognizing human motion posture . However, the existing motion capture technology is generally used in large-scale entertainment equipment, animation production, gait analysis, biomechanics, ergonomics and other fields. With the popularity of mobile devices such as mobile phones and tablet computers, mobile devices such as mobile phones and tablet computers Simple, convenient, and not limited by time and place, it has become a must-have for people's entertainment, and it is an urgent problem to realize motion capture with good display and interactive effects in mobile devices such as mobile phones and tablet computers.

Contents of the invention

The embodiment of the first aspect of the present disclosure provides a method for determining an action matching result in human-computer interaction, including:

Display the instruction image on the display unit, and collect the motion information of the person;

Calculate the total score by calculating the action information and the pre-stored template every set time;

A matching result corresponding to the total score is displayed on the display unit.

Preferably, the total score includes a matching score; wherein, the matching score is obtained by the following steps:

Extract multiple single-frame images from the action images in the action information at set time intervals;

matching each of the single-frame images with the pre-stored template;

The matching score is calculated according to the matching ratios of the plurality of single-frame images and the template.

Preferably, the total score also includes an offset score; the offset score is obtained by the following steps:

The offset score is calculated according to the time when the person performs the action in the action information and the set time.

Preferably, the formula for calculating the offset score is calculated according to the time when the person does the action in the action information and the set time:

ΔT = |T ₁ -T ₂ |;

T _bias is the offset score; ΔT is the offset time; T ₁ is the set time; X is a random constant, and X>0; T ₂ is the time when the person in the action information performs the action.

Preferably, the total score also includes a pre-stored random score.

Preferably, the formula for calculating the total score is:

T _total = N ₁ * T _horse + N ₂ * T _partial + N ₃ * T _with ;

N ₁ +N ₂ +N ₃ = 100%;

T _total is the total score, T _match is the matching score, T _bias is the offset score, T _random is the random score, N ₁ , N ₂ and N ₃ are random percentages, and N ₁ > 0, N ₂ ≥ 0, N ₃ ≥0.

Preferably, displaying the matching result corresponding to the total score on the display unit specifically includes:

Scores and/or animations corresponding to the total points are displayed on the display unit.

The embodiment of the second aspect of the present disclosure provides a device for determining action matching results in human-computer interaction, including: an interaction module, configured to display an instruction image on a display unit, and collect human action information; a scoring module, used for each Computing the action information and the pre-stored template at intervals of a set time to obtain a total score; and an execution module, configured to control displaying a matching result corresponding to the total score on the display unit.

Preferably, the scoring module includes: an extraction unit, configured to extract a plurality of single-frame images from the action images in the action information at set time intervals; a matching unit, configured to compare each of the single-frame images with The pre-stored template matching; the matching score unit is used to calculate the matching score according to the matching ratio between the multiple single-frame images and the template; and the total score unit is used to calculate the matching score according to the matching score. Total Score.

Preferably, the scoring module further includes: an offset score unit, configured to calculate an offset score based on the time when a person performs an action in the action information and the set time; the total score unit calculates an offset score based on the offset The shift score and the matching score are calculated to obtain the total score.

Preferably, the scoring module further includes: a random scoring unit, which is used to extract a pre-stored random score; the total score unit calculates the total score according to the offset score, the matching score and the random score .

The embodiment of the third aspect of the present disclosure provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method for determining an action matching result in human-computer interaction described in any one of the above-mentioned methods is implemented. step.

The embodiment of the fourth aspect of the present disclosure provides a human-computer interaction device, including a memory, a processor, and a program stored in the memory and operable on the processor. When the processor executes the program, any of the above-mentioned The steps of the method for determining the action matching result in the human-computer interaction described in the item.

According to the technical solution provided by the present invention, the display unit (the display unit can be a display screen, etc.) displays instruction images (such as a plurality of stick figures in different postures, animations, animal images, etc.), and the user performs the same body movements as these instruction images , so that the user forms a dancing action, and at the same time, collect the user's image, compare and match the human action image with the coordinate points, and calculate the total score according to the human action information and the pre-stored template, and match the corresponding total score The results (such as scores and/or animation special effects) are displayed on the display unit, which can guide users who are not very good at dancing, so that users can do standard dance moves, which improves the entertainment effect, thereby improving the user's experience effect; in addition , each time the user completes an action, the user's action is compared with the pre-stored template. This detection method can achieve accurate detection, improve the detection accuracy of the product, and thus improve the experience of the product.

Additional aspects and advantages of the disclosure will become apparent in the description which follows, or may be learned by practice of the disclosure.

Description of drawings

The above and/or additional aspects and advantages of the present disclosure will become apparent and comprehensible from the description of the embodiments in conjunction with the following drawings, in which:

FIG. 1 is a schematic diagram of a hardware structure of a terminal device according to an embodiment of the present disclosure;

Fig. 2 is a structural block diagram of a first embodiment of an action matching result determination device in human-computer interaction according to the present disclosure;

Fig. 3 is a structural block diagram of a second embodiment of the device for determining action matching results in human-computer interaction according to the present disclosure;

Fig. 4 is a structural block diagram of a third embodiment of an action matching result determining device in human-computer interaction according to the present disclosure;

Fig. 5 is a structural block diagram of a fourth embodiment of an action matching result determination device in human-computer interaction according to the present disclosure;

FIG. 6 is a flow chart of the first embodiment of the method for determining action matching results in human-computer interaction in the present disclosure;

FIG. 7 is a flow chart of the second embodiment of the method for determining action matching results in human-computer interaction in the present disclosure;

FIG. 8 is a flow chart of a third embodiment of the method for determining action matching results in human-computer interaction according to the present disclosure;

FIG. 9 is a flowchart of a fourth embodiment of the method for determining action matching results in human-computer interaction according to the present disclosure;

10 is a schematic diagram of a computer-readable storage medium according to an embodiment of the present disclosure;

Fig. 11 is a schematic structural diagram of a human-computer interaction device according to an embodiment of the present disclosure.

Wherein, the corresponding relationship between reference numerals and component names in Fig. 1 to Fig. 5, Fig. 10 and Fig. 11 is:

Result determination device 100, interaction module 101, scoring module 102, extraction unit 1021, matching unit 1022, matching scoring unit 1023, total scoring unit 1024, offset scoring unit 1025, random scoring unit 1206, execution module 103, 1 wireless communication unit , 2 input unit, 3 user input unit, 4 sensing unit, 5 output unit, 6 memory, 7 interface unit, 8 controller, 9 power supply unit, 80 human-computer interaction device, 801 memory, 802 processor, 900 computer can For reading a storage medium, step 901 is a non-transitory computer readable instruction.

Detailed ways

In order to understand the above-mentioned purpose, features and advantages of the present disclosure more clearly, the present disclosure will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

In the following description, many specific details are set forth in order to fully understand the present disclosure. However, the present disclosure can also be implemented in other ways different from those described here. Therefore, the protection scope of the present disclosure is not limited by the specific details disclosed below. EXAMPLE LIMITATIONS.

The following discussion provides several embodiments of the disclosure. Although each embodiment represents a single inventive combination, different embodiments of the disclosure may be substituted, or combined, and thus the disclosure may also be considered to encompass all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes A, B, C, and another embodiment includes a combination of B and D, then the disclosure should also be considered to include all other possible combinations including one or more of A, B, C, D Although this embodiment may not be clearly written in the following content.

As shown in Figure 1, the human-computer interaction device, that is, the terminal equipment can be implemented in various forms, and the terminal equipment in the present disclosure can include but not limited to mobile phones, smart phones, notebook computers, digital broadcast receivers, PDA (personal digital assistant), PAD (tablet computer), PMP (portable multimedia player), navigation device, vehicle-mounted terminal equipment, vehicle-mounted display terminal, vehicle-mounted electronic rearview mirror, etc., and mobile terminal equipment such as digital TV, desktop computer, etc. Fixed terminal equipment.

In an embodiment of the present disclosure, a terminal device may include a wireless communication unit 1,

An A/V (audio/video) input unit 2, a user input unit 3, a sensing unit 4, an output unit 5, a memory 6, an interface unit 7, a controller 8, a power supply unit 9, and the like. Wherein, the A/V (audio/video) input unit 2 includes, but is not limited to, a camera, a front camera, a rear camera, and various audio and video input devices. Those skilled in the art should understand that the components included in the terminal device listed in the above embodiments are not limited to the above-mentioned types, and may include fewer or more components.

Those skilled in the art will appreciate that the various embodiments described herein can be implemented on a computer-readable medium using, for example, computer software, hardware, or any combination thereof. For hardware implementation, the embodiments described herein can be implemented by using Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays ( FPGA), processors, controllers, microcontrollers, microprocessors, electronic units designed to perform the functions described herein, and in some cases, such implementations may be implemented in a controller implement. For software implementation, an embodiment such as a procedure or a function may be implemented with a separate software module that allows at least one function or operation to be performed. The software codes can be implemented by a software application (or program) written in any suitable programming language, stored in memory and executed by a controller.

As shown in FIG. 2 , the device 100 for determining an action matching result in human-computer interaction provided by the embodiment of the first aspect of the present disclosure includes: an interaction module 101 , a scoring module 102 and an execution module 103 .

Specifically, the interaction module 101 is used to display the instruction image on the display unit, and collect the action information of the person; the scoring module 102 is used to calculate the total score by calculating the action information and the pre-stored template every set time; the execution module 103 It is used for controlling to display the matching result corresponding to the total score on the display unit.

In the device for determining action matching results in human-computer interaction provided by the present disclosure, the display unit (the display unit can be a display screen, etc.) displays instruction images (such as multiple stick figures in different postures, animations, animal images, etc.), and the user does The same body movements as these instruction images make the user dance. At the same time, the interaction module collects the user's image, and the comparison module matches the person's movement image with the coordinate points, and calculates it based on the person's movement information and the pre-stored template. The total score and the corresponding matching result (such as score and/or animation special effects) are displayed on the display unit, which has a guiding effect on users who are not very good at dancing, enables users to do standard dance moves, and improves entertainment. effect, thereby improving the user experience effect; in addition, each time the user completes an action, the scoring module compares the user's action with the pre-stored template. This detection method can achieve accurate detection and improve the detection accuracy of the product. product experience.

In one embodiment of the present disclosure, as shown in FIG. 3 , the scoring module 102 includes an extraction unit 1021 , a matching unit 1022 , a matching scoring unit 1023 and a total scoring unit 1024 .

Specifically, the extraction unit 1021 is used to extract a plurality of single-frame images from the action images in the action information every set time; the matching unit 1022 is used to match each single-frame image with a pre-stored template; the matching score unit 1023 It is used to calculate and obtain the matching score according to the matching ratios of multiple single-frame images and the template; the total score unit 1024 is used to calculate and obtain the total score according to the matching scores.

In this embodiment, the extraction unit 1021 extracts a plurality of single-frame images from the action images in the action information every set time, such as taking one hundred frame images per unit time; the matching unit 1022 compares the one hundred frame images with the pre-stored template matching; judging the coincidence rate of one hundred frames of images, this detection method can achieve accurate detection, improve the detection accuracy of products, thereby improving the product experience effect; the matching scoring unit 1023 The matching rate is calculated to obtain a matching score, such as 60 points, 70 points, 80 points or 90 points, etc.; the total score unit 1024 is calculated according to the matching score to obtain a total score, such as 75 points, 80 points, 85 points, 90 points, 95 points, etc.

In one embodiment of the present disclosure, as shown in FIG. 4 , the scoring module includes: the scoring module 102 includes an extraction unit 1021 , a matching unit 1022 , a matching scoring unit 1023 , an offset scoring unit 1025 and a total scoring unit 1024 .

Specifically, the extraction unit 1021 is used to extract a plurality of single-frame images from the action images in the action information every set time; the matching unit 1022 is used to match each single-frame image with a pre-stored template; the matching score unit 1023 It is used to calculate the matching score according to the matching rate of a plurality of single-frame images and the template; the offset score unit 1025 is used to calculate the offset score according to the time when the person in the action information performs an action and the set time; the total score unit 1024 uses The total score is calculated based on the offset score and the matching score.

In this embodiment, the extraction unit 1021 extracts a plurality of single-frame images from the action images in the action information every set time, such as taking one hundred frame images per unit time; the matching unit 1022 compares the one hundred frame images with the pre-stored template matching; judging the coincidence rate of one hundred frames of images, this detection method can achieve accurate detection, improve the detection accuracy of products, thereby improving the product experience effect; the matching scoring unit 1023 The matching rate is calculated to obtain a matching score (such as 60 points, 70 points, 80 points or 90 points, etc.), and the user action and the pre-stored template in the template; the offset score unit 1025 is based on the time and setting of the person in the action information. The time is calculated to obtain the offset score, such as 60 points, 70 points, 80 points or 90 points, etc.; the total score unit 1024 is calculated according to the offset score and the matching score to obtain the total score, such as 75 points, 80 points, 85 points, 90 points, 95 points etc.

In one embodiment of the present disclosure, as shown in FIG. 5 , the scoring module includes: the scoring module 102 includes an extraction unit 1021, a matching unit 1022, a matching scoring unit 1023, an offset scoring unit 1025, a random scoring unit 1206 and a total scoring unit 1024.

Specifically, the extraction unit 1021 is used to extract a plurality of single-frame images from the action images in the action information every set time; the matching unit 1022 is used to match each single-frame image with a pre-stored template; the matching score unit 1023 It is used to calculate the matching score according to the matching rate of a plurality of single-frame images and the template; the offset score unit 1025 is used to calculate the offset score according to the time when the person in the action information performs an action and the set time; the random score unit 1206 uses Based on the extracted pre-stored random score; the total score unit 1024 is used to calculate the total score according to the offset score and the matching score.

In this embodiment, the extraction unit 1021 extracts a plurality of single-frame images from the action images in the action information every set time, such as taking one hundred frame images per unit time; the matching unit 1022 compares the one hundred frame images with the pre-stored template matching; judging the coincidence rate of one hundred frames of images, this detection method can achieve accurate detection, improve the detection accuracy of products, thereby improving the product experience effect; the matching scoring unit 1023 The matching rate is calculated to obtain a matching score, such as 60 points, 70 points, 80 points or 90 points, etc.; the offset score unit 1025 is calculated according to the time when the person in the action information performs an action and the set time to obtain an offset score, such as 60 points, 70 points, 80 points or 90 points, etc.; the pre-stored random scores extracted by the random score unit 1206, such as 60 points, 70 points, 80 points or 90 points, etc.; the total score unit 1024 is calculated according to the offset score, matching score and random score Get the total score, such as 75 points, 80 points, 85 points, 90 points, 95 points, etc.

Example 1

As shown in FIG. 6, the embodiment of the second aspect of the present disclosure provides a method for determining an action matching result in human-computer interaction, including:

Step 10, displaying an instruction image on the display unit, and collecting motion information of the person;

Step 20, calculate the total score by calculating the action information and the pre-stored template every set time;

Step 30, displaying the matching result corresponding to the total score on the display unit.

In the method for determining the action matching result in human-computer interaction provided by the present disclosure, the display unit (the display unit can be a display screen, etc.) displays instruction images (such as multiple stick figures in different postures, animations, animal images, etc.), and the user can do it. The same body movements as these instruction images make the user dance. At the same time, the user's image is collected, the person's movement image is matched with the coordinate points, and the total score is calculated according to the person's movement information and the pre-stored template. The matching results (such as scores and/or animation special effects) corresponding to the total score are displayed on the display unit, which guides users who are not very good at dancing, enables users to do standard dance moves, improves the entertainment effect, and improves In addition, every time the user completes an action, the user's action is compared with the pre-stored template. This detection method can achieve accurate detection, improve the detection accuracy of the product, and thus improve the product experience effect.

Embodiment two

As shown in FIG. 7, in one embodiment of the present disclosure, step 20 includes:

Step 21, extracting a plurality of single-frame images from the action images in the action information every set time;

Step 22, matching each single-frame image with a pre-stored template;

Step 23, calculating the total score according to the matching ratios of multiple single-frame images and the template.

In this embodiment, the method for determining the action matching result in human-computer interaction includes:

Step 10, displaying an instruction image on the display unit, and collecting motion information of the person;

Step 21, extracting a plurality of single-frame images from the action images in the action information every set time;

Step 22, matching each single-frame image with a pre-stored template;

Step 23, calculating the total score according to the matching rate of multiple single-frame images and the template;

Step 30, displaying the matching result corresponding to the total score on the display unit.

In this embodiment, multiple single-frame images are extracted from the action images in the action information every set time, such as taking one hundred frame images per unit time; matching one hundred frame images with pre-stored templates; judging one The overlap rate of 100 frames of images, this detection method can achieve accurate detection, improve the detection accuracy of the product, thereby improving the product experience effect; calculate the matching score based on the matching rate of 100 frames of images and templates, such as 60 points , 70 points, 80 points or 90 points, etc.; calculate the total score based on the matching score, such as 75 points, 80 points, 85 points, 90 points, 95 points, etc.

Embodiment three

As shown in FIG. 8, in one embodiment of the present disclosure, step 20 includes:

Step 21, extracting a plurality of single-frame images from the action images in the action information every set time;

Step 22, matching each single-frame image with a pre-stored template;

Step 23, calculating the matching score according to the matching ratio of multiple single-frame images and the template;

Step 24, calculate the offset score according to the time when the person in the action information does the action and the set time;

Step 25, calculate the total score according to the offset score and the matching score.

In this embodiment, the method for determining the action matching result in human-computer interaction includes:

Step 10, displaying an instruction image on the display unit, and collecting motion information of the person;

Step 20, step 21, extracting a plurality of single-frame images from the action images in the action information every set time;

Step 22, matching each single-frame image with a pre-stored template;

Step 23, calculating the matching score according to the matching ratio of multiple single-frame images and the template;

Step 24, calculate the offset score according to the time when the person in the action information does the action and the set time;

Step 25, calculating the total score according to the offset score and the matching score;

Step 30, displaying the matching result corresponding to the total score on the display unit.

In this embodiment, multiple single-frame images are extracted from the action images in the action information every set time, such as taking one hundred frame images per unit time; matching one hundred frame images with pre-stored templates; judging one The overlap rate of 100 frames of images, this detection method can achieve accurate detection, improve the detection accuracy of the product, thereby improving the product experience effect; the matching score is calculated according to the matching rate of 100 frames of images and the template (for example, 60 points , 70 points, 80 points or 90 points, etc.), for user actions and pre-stored templates in the template; according to the time of the person doing the action in the action information and the set time, the offset score is calculated, such as 60 points, 70 points, 80 points points or 90 points, etc.; calculate the total score based on the offset score and matching score, such as 75 points, 80 points, 85 points, 90 points, 95 points, etc.

In one embodiment of the present disclosure, the formula for calculating the offset score is calculated according to the time when the person does the action in the action information and the set time:

ΔT = |T ₁ -T ₂ |;

T _bias is the offset score; ΔT is the offset time; T ₁ is the set time; X is a random constant, and X>0; T ₂ is the time when the person in the action information performs the action.

Embodiment Four

As shown in Figure 9, step 21, extracting a plurality of single-frame images from the action images in the action information every set time;

Step 22, matching each single-frame image with a pre-stored template;

Step 23, calculating the matching score according to the matching ratio of multiple single-frame images and the template;

Step 24, calculate the offset score according to the time when the person in the action information does the action and the set time;

Step 25, extracting the prestored random fraction;

Step 26, calculate the total score according to the offset score, the random score and the matching score.

In this embodiment, the method for determining the action matching result in human-computer interaction includes:

Step 10, displaying an instruction image on the display unit, and collecting motion information of the person;

Step 21, extracting a plurality of single-frame images from the action images in the action information every set time;

Step 22, matching each single-frame image with a pre-stored template;

Step 23, calculating the matching score according to the matching ratio of multiple single-frame images and the template;

Step 24, calculate the offset score according to the time when the person in the action information does the action and the set time;

Step 25, extracting the prestored random fraction;

Step 26, calculating the total score according to the offset score, the random score and the matching score;

Step 30, displaying the matching result corresponding to the total score on the display unit.

In this embodiment, multiple single-frame images are extracted from the action images in the action information every set time, such as taking one hundred frame images per unit time; matching one hundred frame images with pre-stored templates; judging one The overlap rate of 100 frames of images, this detection method can achieve accurate detection, improve the detection accuracy of the product, thereby improving the product experience effect; calculate the matching score based on the matching rate of 100 frames of images and templates, such as 60 points , 70 points, 80 points or 90 points, etc.; calculate the offset score based on the time of the person doing the action in the action information and the set time, such as 60 points, 70 points, 80 points or 90 points, etc.; the extracted pre-stored random Score, such as 60 points, 70 points, 80 points or 90 points, etc.; calculate the total score based on the offset score, matching score and random score, such as 75 points, 80 points, 85 points, 90 points, 95 points, etc.

In one embodiment of the present disclosure, the formula for calculating the total score is:

T _total = N ₁ * T _horse + N ₂ * T _partial + N ₃ * T _with ;

N ₁ +N ₂ +N ₃ = 100%;

T _total is the total score, T _match is the matching score, T _bias is the offset score, T _random is the random score, N ₁ , N ₂ and N ₃ are random percentages, and N ₁ > 0, N ₂ ≥ 0, N ₃ ≥0. When the total score does not include the offset score and/or random score, N ₂ and N ₃ are 0, that is, T _total = N ₁ * T _match + N ₃ * T _with N ₁ + N ₃ = 100%; T _total = N ₁ * _T +N ₂ *T _bias , N ₁ +N ₂ =100%; _Ttotal =N ₁ * _T , N ₁ =100%; in some embodiments of the present disclosure, N ₁ (90% )+N ₂ (8%)+N ₃ (2%)=100%, N ₁ (80%)+N ₂ (15%)+N ₃ (5%)=100%, N ₁ (95%)+ N ₂ (3%)+N ₃ (2%)=100%N ₁ (80%)+N ₂ (0%)+N ₃ (10%)=100%; (90%)+N ₂ (10%) )+N ₃ (0%)=100%, (95%)+N ₂ (5%)+N ₃ (0%)=100%, (85%)+N ₂ (15%)+N ₃ (0 %)=100%; (90%)+N ₂ (0%)+N ₃ (10%)=100%, (95%)+N ₂ (0%)+N ₃ (5%)=100%, (980%)+N ₂ (0%)+N ₃ (2%)=100%. Those skilled in the art should understand that there are many combinations of N ₁ , N ₂ and N ₃ , which will not be listed here.

In one embodiment of the present disclosure, displaying the matching result corresponding to the total score on the display unit specifically includes: displaying the score and/or animation corresponding to the total score on the display unit, and the animation can be perfect, good, great , miss and other digital animations, or display special effects such as heart rain and star rain on the display unit. Those skilled in the art should understand that,

As shown in FIG. 10 , the computer-readable storage medium provided by the embodiment of the third aspect of the present disclosure has a computer program stored thereon, and when the program is executed by a processor, the action matching result determination in any of the above-mentioned human-computer interactions can be realized. method steps. Among them, the computer-readable storage medium may include, but is not limited to, any type of disk, including flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), static random access memory (SRAM), electrically erasable Except for programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, floppy disk, compact disk, DVD, CD-ROM, microdrive and magneto-optical disk, ROM, RAM, EPROM, EEPROM, DRAM, VRAM, Flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and/or data. In one embodiment of the present disclosure, a computer readable storage medium 900 has non-transitory computer readable instructions 901 stored thereon. When the non-transitory computer-readable instructions 901 are executed by the processor, the human-computer interaction method based on the dynamic posture of the human body according to the embodiments of the present disclosure described above is executed.

The human-computer interaction device provided by the embodiment of the fourth aspect of the present disclosure includes a memory, a processor, and a program stored on the memory and operable on the processor. When the processor executes the program, any of the above human-computer interaction can be realized. The steps of the method for determining the action matching result.

In one embodiment of the present disclosure, memory is used to store non-transitory computer readable instructions. Specifically, the memory may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include random access memory (RAM) and/or cache memory (cache), etc., for example. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, and the like. In one embodiment of the present disclosure, the processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and/or instruction execution capabilities, and may control other components in the human-computer interaction device to execute expected functionality. In one embodiment of the present disclosure, the processor is configured to execute computer-readable instructions stored in the memory, so that the human-computer interaction device executes the above-mentioned interaction method.

In an embodiment of the present disclosure, as shown in FIG. 11 , a human-computer interaction device 80 includes a memory 801 and a processor 802 . The various components in the human-computer interaction device 80 are interconnected through a bus system and/or other forms of connection mechanisms (not shown).

The memory 801 is used to store non-transitory computer readable instructions. Specifically, the memory 801 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include random access memory (RAM) and/or cache memory (cache), etc., for example. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, and the like.

Processor 802 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and/or instruction execution capabilities, and may control other components in human-computer interaction device 80 to perform desired functions. In one embodiment of the present disclosure, the processor 802 is configured to execute computer-readable instructions stored in the memory 801 , so that the human-computer interaction device 80 executes the above-mentioned human-computer interaction method based on the dynamic posture of the human body. The human-computer interaction device is the same as the above described embodiment of the human-computer interaction method based on the dynamic posture of the human body, and its repeated description will be omitted here.

In one embodiment of the present disclosure, the human-computer interaction device is a mobile device. The camera of the mobile device collects images of the user, and downloads the song and instruction image corresponding to the instruction through the mobile device. After the song and the instruction image are downloaded, the mobile device A recognition frame (the recognition frame can be a human-shaped frame) appears on the display unit of the mobile device. By adjusting the distance between the user and the mobile device, the user's image is placed in the recognition frame. displayed as graphics such as bright spots, stars, rings, etc.), the user starts to do dance movements so that his body movements match these instruction images, and according to the matching degree of the user's actions with the instruction images, the score and/or points are displayed on the display unit Or animation (animation can be digital animations such as perfect, good, great, miss, or from displaying special effects such as heart rain and star rain on the display unit), after the music is played, the display unit of the mobile device will display scores and grades, Users can download or share their own dance videos or enter the ranking list, and the mobile devices can be mobile phones, tablet computers, etc.

In the present disclosure, the term "plurality" refers to two or more, unless otherwise clearly defined. The terms "installation", "connection", "connection", "fixed" and other terms should be interpreted in a broad sense, for example, "connection" can be fixed connection, detachable connection, or integral connection; "connection" can be directly or indirectly through an intermediary. Those of ordinary skill in the art can understand the specific meanings of the above terms in the present disclosure according to specific situations.

In the description of this specification, descriptions of the terms "one embodiment", "some embodiments", "specific embodiments" and the like mean that specific features, structures, materials or characteristics described in connection with the embodiment or example are included in the present disclosure In at least one embodiment or example of . In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The above descriptions are only preferred embodiments of the present disclosure, and are not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present disclosure shall be included within the protection scope of the present disclosure.

Claims (13)

1. A method for determining an action matching result in human-computer interaction, comprising: Display the instruction image on the display unit, and collect the motion information of the person; Calculate the total score by calculating the action information and the pre-stored template every set time; A matching result corresponding to the total score is displayed on the display unit. 2. The action matching result determination method in human-computer interaction according to claim 1, characterized in that, said total score includes a matching score; Wherein, the matching score is obtained by the following steps: Extract multiple single-frame images from the action images in the action information at set time intervals; matching each of the single-frame images with the pre-stored template; The matching score is calculated according to the matching ratios of the plurality of single-frame images and the template. 3. The action matching result determination method in human-computer interaction according to claim 2, characterized in that, The total score also includes an offset score; the offset score is obtained by the following steps: The offset score is calculated according to the time when the person performs the action in the action information and the set time. 4. The method for determining the action matching result in human-computer interaction according to claim 3, characterized in that, the calculation formula of the offset score is calculated according to the time when the person in the action information performs the action and the set time for: ΔT = |T ₁ -T ₂ |; T _bias is the offset score; ΔT is the offset time; T ₁ is the set time; X is a random constant, and X>0; T ₂ is the time when the person in the action information performs the action. 5. The action matching result determination method in human-computer interaction according to claim 3, characterized in that, The total score also includes a pre-stored random score. 6. The action matching result determination method in human-computer interaction according to claim 5, characterized in that, The formula for calculating the total score is: T _total = N ₁ * T _horse + N ₂ * T _partial + N ₃ * T _with ; N ₁ +N ₂ +N ₃ = 100%; T _total is the total score, T _match is the matching score, T _bias is the offset score, T _random is the random score, N ₁ , N ₂ and N ₃ are random percentages, and N ₁ > 0, N ₂ ≥ 0, N ₃ ≥0. 7. The method for determining the action matching result in human-computer interaction according to claim 1, wherein displaying the matching result corresponding to the total score on the display unit specifically comprises: Scores and/or animations corresponding to the total points are displayed on the display unit. 8. A device for determining action matching results in human-computer interaction, characterized in that it comprises: The interactive module is used for displaying instruction images on the display unit and collecting human action information; A scoring module, configured to calculate the action information and the pre-stored template every set time to obtain a total score; and An execution module, configured to control displaying the matching result corresponding to the total score on the display unit. 9. The device for determining action matching results in human-computer interaction according to claim 8, characterized in that, The scoring modules include: an extracting unit, configured to extract a plurality of single-frame images from the action images in the action information at set time intervals; a matching unit, configured to match each of the single-frame images with the pre-stored template; a matching scoring unit, configured to calculate a matching score according to the matching ratios between a plurality of single-frame images and the template; and A total score unit, configured to calculate the total score according to the matching score. 10. The device for determining action matching results in human-computer interaction according to claim 9, wherein: The scoring module also includes: An offset score unit, configured to calculate an offset score according to the time when the person in the action information performs an action and the set time; The total score unit calculates the total score according to the offset score and the matching score. 11. The device for determining action matching results in human-computer interaction according to claim 10, characterized in that, The scoring module also includes: Random scoring unit, used to extract pre-stored random scores; The total score unit calculates the total score according to the offset score, the matching score and the random score. 12. A computer-readable storage medium, on which a computer program is stored, characterized in that, when the program is executed by a processor, the action matching result in the human-computer interaction according to any one of claims 1-7 is realized Determine the steps of the method. 13. A human-computer interaction device, comprising a memory, a processor, and a program stored in the memory and operable on the processor, characterized in that, when the processor executes the program, the claims 1-7 are realized The steps of the method for determining the action matching result in any one of the human-computer interaction.