Photographing method, wearable device, and readable storage medium

Abstract

The application relates to the technical field of wearable devices, and provides a photographing method, a wearable device and a computer readable storage medium. The application monitors the state change of a user based on a user motion parameter, monitors important events in a photographed image based on an event importance parameter, and monitors the change amplitude of a photographing scene based on a scene change parameter, that is, the target priority is obtained from multiple dimensions such as the user motion parameter, the event importance score and the scene change parameter, and the photographing parameters of a photographing device in the wearable device are dynamically adjusted based on the target priority. Therefore, the wearable device adaptively adjusts the photographing parameters under different motions and scenes, reduces the amount of redundant recording data while ensuring the recording quality of key events, reduces the energy consumption of the wearable device when photographing non-key content, and prolongs the service life of the wearable device.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wearable devices, and particularly relates to a photographing method, a wearable device and a computer readable storage medium. BACKGROUND

[0002] With the increasing popularity of wearable devices, the demand of users for photographing images or videos anytime and anywhere is increasingly obvious. However, long-time recording at high frame rate and high resolution brings serious power consumption pressure to wearable recording devices. Therefore, how to improve the endurance time of wearable recording devices while ensuring the recording effect is a problem to be solved for wearable recording devices at present. SUMMARY

[0003] The main purpose of the present application is to provide a photographing method, a wearable device and a computer readable storage medium, which aims to improve the endurance time of wearable recording devices.

[0004] To achieve the above-mentioned purpose, the present application provides a photographing method, which comprises the following steps:

[0005] obtaining a user motion parameter of the wearable device;

[0006] obtaining a scene change parameter of an environment in which the wearable device is located, and obtaining an event importance parameter of the wearable device;

[0007] calculating a target priority according to the user motion parameter, the scene change parameter and the event importance parameter;

[0008] adjusting a photographing parameter of a photographing device of the wearable device according to the target priority, and photographing according to the adjusted photographing parameter.

[0009] In addition, to achieve the above-mentioned purpose, the present application further provides a computer device, which comprises a processor, a memory and a photographing program stored in the memory and executable by the processor, wherein when the photographing program is executed by the processor, the steps of the photographing method as described above are implemented.

[0010] In addition, to achieve the above-mentioned purpose, the present application further provides a computer readable storage medium, which stores a photographing program, wherein when the photographing program is executed by a processor, the steps of the photographing method as described above are implemented.

[0011] The present application provides a shooting method, which is applied to a wearable device. The method obtains user motion parameters of the wearable device; obtains scene change parameters of the environment in which the wearable device is located, and obtains event importance parameters of the wearable device; calculates a target priority based on the user motion parameters, the scene change parameters, and the event importance parameters; adjusts the shooting parameters of the wearable device's shooting device based on the target priority, and shoots according to the adjusted shooting parameters. Through the above-mentioned method, the present application monitors changes in user status based on user motion parameters, monitors important events in captured images based on event importance parameters, and monitors the magnitude of changes in captured scenes based on scene change parameters. That is, the target priority is obtained from multiple dimensions such as user motion parameters, event importance scores, and scene change parameters, and the shooting parameters of the wearable device's shooting device are dynamically adjusted based on the target priority. As a result, the wearable device can adaptively adjust its shooting parameters under different motions and scenes, while ensuring the quality of the wearable device's recording of key events, reducing the amount of recorded redundant data, reducing the energy consumption of the wearable device when shooting non-critical content, and thus improving the battery life of the wearable device. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 Schematic diagram of the process of the first embodiment of the photographing method of the present invention;

[0013] Figure 2 Schematic diagram of the process of the second embodiment of the photographing method of the present invention;

[0014] Figure 3 1 is a flow chart of a third embodiment of a photographing method according to the present invention;

[0015] Figure 4 Schematic diagram of the hardware structure of the wearable device involved in the embodiment of the present invention.

[0016] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0018] The flowcharts shown in the drawings are merely illustrative and do not necessarily include all the contents and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can be further decomposed, combined or partially merged, so the actual execution order can be changed according to actual conditions.

[0019] It should be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and the appended claims of the present application, the singular forms "a", "an" and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0020] It should also be understood that the term "and / or" used in the specification and the appended claims of the present application means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0021] The photographing method related to the embodiments of the present application is mainly applied to a wearable device, which can be smart glasses, a head-mounted display or other wearable devices with photographing functions.

[0022] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The following embodiments and features in the embodiments can be combined with each other without conflict.

[0023] Referring to Figure 1 , Figure 1 The flowchart of the first embodiment of the photographing method of the present application is shown.

[0024] As Figure 1 shown, the embodiment of the present application provides a photographing method applied to a wearable device, which includes: a motion sensor for collecting the body movement amplitude of a user; an eye movement sensor for collecting eye movement data of the user, such as eye movement amplitude; a photographing device, such as a camera sensor, for photographing videos or images; a processing unit including a low-power real-time processor and a high-performance processor for periodically analyzing the data collected by the motion sensor and the eye movement sensor and the photographing performed by the photographing device. It can also include a biological sensor for collecting biological parameters of the user, such as heart rate, blood pressure and body temperature. The following will be described taking smart glasses as an example.

[0025] In an embodiment, the photographing method includes steps S10 to S40.

[0026] Step S10, obtaining the user motion parameters of the wearable device;

[0027] In this embodiment, the acquired user motion parameters can be collected in real time by the sensor, that is, reading the user motion parameters of the user at the current time, or collected by the sensor at a preset period, that is, reading the user motion parameters collected by the sensor in a preset period. The user motion parameters include user body motion amplitude parameters and user eye movement amplitude parameters. When the body motion amplitude data S1 and the eye movement amplitude data S2 are read, the body motion amplitude data S1 and the eye movement amplitude data S2 are filtered and normalized, and the body motion amplitude data S1 and the user eye movement amplitude data S2 are normalized to [0, 10]. Wherein, the closer the body motion amplitude data S1 is to 10, the more intense the user's body motion is. The closer the eye movement amplitude data S2 is to 10, the more frequent the user's line of sight movement or focus point shift is.

[0028] Step S20, acquiring a scene change parameter of an environment where the wearable device is located, and acquiring an event importance parameter of the wearable device;

[0029] In this embodiment, the scene change parameter S3 can be the scene change amplitude of the environment (such as the shooting scene) where the smart glasses are located corresponding to the current time and the last time. It can also be the scene change amplitude of the environment where the smart glasses are located in a preset period. The scene change parameter S3 includes light intensity change and temperature change.

[0030] Further, the light change parameter of the environment where the wearable device is located can be detected by optical flow or image difference method, or the ambient light change is detected by photosensitive sensor to obtain the light intensity change amplitude, and the temperature change parameter of the environment where the wearable device is located is detected by temperature sensor to obtain the temperature change amplitude.

[0031] The event importance parameter S4 can be the event importance parameter corresponding to the shooting image of the smart glasses at the current time, and can also be the event importance parameter corresponding to multiple shooting images of the smart glasses in a preset period.

[0032] After acquiring the scene change parameter S3 and the event importance parameter S4, the scene change parameter S3 and the event importance parameter S4 are normalized, and the scene change parameter S3 and the event importance parameter S4 are normalized to [0, 100]. The closer the scene change parameter S3 is to 100, the greater the scene change amplitude of the environment where the smart glasses are located. The closer the event importance parameter S4 is to 100, the higher the key event importance in the shooting image at the current time or in the preset period.

[0033] Further, the shooting method further comprises:

[0034] acquire a parameter acquisition period corresponding to the user motion parameter, the scene change parameter and the event importance parameter respectively;

[0035] Based on the parameter acquisition period, the user motion parameter, the scene change parameter and the event importance parameter are collected or updated respectively.

[0036] In this embodiment, in order to further balance the shooting quality of key events and reduce the power consumption of the device, different parameter acquisition periods are set for each parameter, and based on the parameter acquisition period, different sensors are set with different cycle frequencies (i.e. working periods). The higher the cycle frequency, the shorter the working period, the faster the data update speed, the faster the response of the shooting parameter adjustment event, and the greater the power consumption of the device.

[0037] In specific embodiments, the parameter acquisition period can also be determined according to the data reading frequency. The higher the data reading frequency, the higher the data acquisition frequency of the sensor, and the shorter the parameter acquisition period.

[0038] The parameter acquisition period of the event importance parameter can be increased in the analysis frequency of the event importance parameter when the acquisition period of any one of the user motion parameter or the scene change parameter is shortened, or within a preset time period after the key event is identified, the analysis frequency of the event importance parameter is increased, and the acquisition period of the event importance parameter is shortened, so as to shorten the response time of the key event.

[0039] In more embodiments, a fixed period can be used as the acquisition period. For example:

[0040] S1 and S2 are collected at a high frequency, such as a parameter acquisition period of every second or several seconds, tens of seconds, etc., which is used to provide the latest data to the calculation of the priority or event importance parameter in real time;

[0041] S3 is collected at a medium frequency, such as a parameter acquisition period of several minutes or tens of minutes, etc., which is used for periodic scene change analysis, and S3 is periodically corrected or updated.

[0042] S4 is collected at a low frequency, such as a parameter acquisition period of 30 minutes, 1 hour or 2 hours, etc., which is used for event importance scoring based on S1, S2 and S3, and further based on the scoring result to identify key frames.

[0043] Step S30, according to the user motion parameter, the scene change parameter and the event importance parameter, calculate the target priority;

[0044] In the embodiment, each value corresponding to the user motion parameter, the scene change parameter and the event importance parameter is substituted into the priority calculation formula to obtain the target priority. The higher the priority, the more important the image to be captured by the smart glasses, and the shooting parameters of the shooting device of the smart glasses need to be improved, such as the frame rate, the resolution and the like, so as to improve the image quality of the captured image. The lower the priority, the less important the image to be captured by the smart glasses, and the shooting device can be controlled to enter a low-power state, such as reducing the frame rate, the resolution and the like, so as to reduce the power consumption of the shooting device.

[0045] In step S40, the shooting parameters of the shooting device of the wearable device are adjusted according to the target priority, and the shooting is performed according to the adjusted shooting parameters.

[0046] In the embodiment, the shooting parameters include basic image parameters such as the frame rate and the resolution, environment adaptive parameters such as the exposure control and the anti-shake parameter, and user interaction parameters such as the shooting model and the focusing parameter.

[0047] The adjustment mode of the shooting parameters can be to compare the target priority with the average priority (or the basic priority). If the target priority is less than the average priority, the shooting parameters are reduced, and the greater the difference, the greater the reduced value. If the target priority is greater than the average priority, the shooting parameters are increased, and the greater the difference, the greater the increased value. The adjustment mode of the shooting parameters can also be to calculate the adjusted target shooting parameters based on the target priority, and to improve or reduce the shooting parameters to the target shooting parameters. The shooting device is controlled to perform the shooting with the target shooting parameters.

[0048] The embodiment provides a photographing method applied to a wearable device, the method comprises the following steps: acquiring a user motion parameter of the wearable device; acquiring a scene change parameter of an environment where the wearable device is located, and acquiring an event importance parameter of the wearable device; calculating a target priority according to the user motion parameter, the scene change parameter and the event importance parameter; adjusting a photographing parameter of a photographing device of the wearable device according to the target priority, and photographing according to the adjusted photographing parameter. In the foregoing manner, the application monitors a user state change condition based on a user motion parameter, monitors an important event in a photographed image based on an event importance parameter, and monitors a photographing scene change amplitude based on a scene change parameter, that is, a target priority is obtained from multiple dimensions such as a user motion parameter, an event importance score and a scene change parameter, and the photographing parameter of the photographing device in the wearable device is dynamically adjusted based on the target priority. Therefore, the wearable device adaptively adjusts the photographing parameter under different motions and scenes, ensures the recording quality of a key event of the wearable device, reduces the amount of redundant recording data, reduces the energy consumption of the wearable device when photographing non-key content, and thus prolongs the endurance time of the wearable device.

[0049] Reference Figure 2 , Figure 2 FIG. 2 is a flowchart of a photographing method according to a second embodiment of the application.

[0050] In the embodiment, the step S30 comprises:

[0051] The step S31 comprises: acquiring a scene type of an environment where the wearable device is located, and determining an adjustment coefficient corresponding to the user motion parameter, the event importance parameter and the scene change parameter respectively based on the scene type.

[0052] The step S32 comprises: calculating the target priority based on each adjustment coefficient, the user motion parameter, the event importance parameter and the scene change parameter.

[0053] The step of calculating the target priority according to the user motion parameter, the scene change parameter and the event importance parameter comprises:

[0054] The step of calculating the target priority according to the user motion parameter, the scene change parameter and the event importance parameter comprises:

[0055] In this embodiment, different parameters have different importance in different shooting scenes. For example, in medical monitoring scenes and public security monitoring scenes, user motion parameters are particularly important, while in daily life scenes, scene change parameters are particularly important. Therefore, based on the scene type of the environment in which the wearable device is located, the adjustment coefficients of the user motion parameters, the event importance parameters and the scene change parameters can be determined, so as to increase the proportion of the corresponding parameters in the priority as needed, and improve the adjustment sensitivity of the shooting parameters.

[0056] In addition, the adjustment coefficient of the user motion parameter can also be determined according to the user state of the user wearing the smart glasses or according to the scene to which the smart glasses belong. For example, when it is detected that the user is sitting for a long time or sleeping, or the scene belongs to a daily life scene, the adjustment coefficient of the user motion parameter is reduced, and the adjustment coefficients of the scene change parameter and the event importance parameter are increased. When it is detected that the user is in high-intensity exercise such as running or playing ball, or in a medical monitoring scene, the adjustment coefficient of the user motion parameter is increased, and the adjustment coefficient of the event importance parameter is reduced.

[0057] The logarithm is removed, and a pure multiplicative formula is used as the priority calculation formula. The calculation formula of the priority P is:

[0058]

[0059] Among them, is the body motion amplitude , is the eye movement amplitude , is the scene change parameter 3 and is the event importance parameter in the adjustment parameter in the priority calculation, is the exponential parameter of the event importance parameter, which is used to amplify or suppress the event importance. Among them;

[0060] When > 1, the influence of the event importance parameter in the priority is amplified or suppressed by power;

[0061] When < 1, the influence of the event importance parameter in the priority is moderately smoothed;

[0062] When = 1, the influence of the event importance parameter in the priority is linearly amplified.

[0063] It can be understood that the calculation of the event importance parameter can be further based on biological parameters such as the heart rate, blood pressure and body temperature of the user, or the priority calculation can be based on biological parameters such as the heart rate, blood pressure and body temperature of the user.

[0064] In the above manner, the embodiment determines the adjustment parameter corresponding to each parameter based on the importance of each parameter in different shooting scenes, thereby improving the influence proportion of the corresponding parameter in the priority, and further adaptively adjusting the shooting parameter based on different parameters in different shooting scenes, thereby improving the adjustment accuracy of the shooting parameter.

[0065] Further, the obtaining the event importance parameter of the wearable device comprises:

[0066] The event importance parameter is calculated based on a preset event scoring model, the user motion parameter, and the scene change parameter.

[0067] The event importance parameter is calculated based on a preset event scoring model, the user motion parameter, and the scene change parameter.

[0068] When the frame rate in the shooting parameter is lower than the minimum frame rate, key frames are extracted from the shooting images of the wearable device based on a preset period to obtain a key frame set, and the event scoring model is trained based on the key frame set.

[0069] In the embodiment, the event scoring model is a multi-modal model, which scores the event in the image in multiple dimensions in combination with the user motion parameter and the scene change parameter. First, images containing various subjects (such as faces, license plates, medical devices, etc.) are screened out, and multi-dimensional analysis is performed on the subject rarity (such as abnormal devices, wild animals, etc.), the scene change amplitude of the fingertips of each frame of image, abnormal behavior (such as sudden events such as falling, gathering, fire, etc.), the body motion amplitude of the user, the eye movement amplitude, the heart rate change amplitude, the body temperature change amplitude, and the audio corresponding to the image in the video to obtain the event importance parameter. The more combined sub-events in the event, the higher the level of the event, i.e., the higher the score, and the score exceeding the threshold is a key event, such as motion intensity (ski jumping), facial expression (smiling), and audio excitement (cheering), which obtains a high-level key event and can be marked as “best moment”, and audio (children's laughter) and user action (chasing scene) obtain a high-level key event and can be marked as “family interaction moment”.

[0070] Specific scoring rules include but are not limited to: the greater the motion amplitude, the higher the corresponding event score; the larger the face size of the target user in the image, the higher the corresponding event score; the higher the audio, the higher the corresponding event score, etc. Other dimensional parameters such as different shooting areas (such as home, hospital), different time periods (such as late at night, during a meeting, etc.), can also be combined to give points to the event, and the event can also be scored based on user state (such as sudden increase in heart rate, abnormal body temperature, etc.); it can also be based on specific characters (such as the user himself, a doctor or a family member, etc.) or abnormal sounds (glass breaking, screaming, etc.) to score the event.

[0071] In specific embodiments, the event importance parameter can also be generated directly based on the preset image semantics.

[0072] For example, the event importance parameter of the wearable device is obtained by:

[0073] The event importance parameter is generated based on the image semantics of the image taken by the wearable device.

[0074] In this embodiment, the image keywords are extracted by OCR, such as text information or image corresponding audio (such as "danger" "first aid") in the picture, or audio containing angry or help-seeking emotions, which can trigger high scores, i.e. generate high event importance scores.

[0075] In more embodiments, the maximum score or the average score of the two event importance parameters can be taken as the final event importance parameter.

[0076] It can be understood that the user can also customize the recording instruction of the key event, such as clapping three times in front of the lens, which can store the key image at high resolution and high frame rate. When the recording instruction of the user's self-defined operation is detected, the priority calculation is not required, and the key image can be directly taken.

[0077] Before the event scoring model scores the taken image, the key image stored in the smart glasses and its server can be obtained to train the event scoring model and improve the scoring accuracy of the event scoring model.

[0078] In order to save the storage space of the smart glasses, the key image can be stored completely, and the non-key image can be stored with the distinguishing point from the key image. Therefore, when it is detected that the shooting device is running at the minimum frame rate all the time, in order to prevent image storage abnormalities caused by too long interval time, the key image is temporarily taken at high resolution and high frame rate when the duration reaches the preset time. In this way, the key frame is extracted every fixed period by the shooting device, and temporarily stored at a higher resolution, which not only provides more training samples for subsequent multi-modal model analysis, but also prevents image storage abnormalities.

[0079] By the above manner, the embodiment performs multi-modal analysis on the event importance of the photographed image from multiple dimensions of the user motion change amplitude, the user body state change amplitude, the shooting scene change amplitude, the sound, and the image semantics in two ways of the image semantic or event scoring model, and the precision of the event importance scoring is improved.

[0080] With reference to Figure 3 , Figure 3 The flowchart of the third embodiment of the photographing method of the present application is shown.

[0081] In the embodiment, the photographing parameter includes a first frame rate, and the step S40 includes:

[0082] In the embodiment, the photographing parameter includes a first frame rate, and the step S40 includes:

[0083] In the embodiment, the photographing parameter includes a first frame rate, and the step S40 includes:

[0084] In the embodiment, the photographing parameter includes a first frame rate, and the step S40 includes:

[0085] In the embodiment, the user mode S5 includes an energy-saving mode, a normal mode, and a motion mode. Different user modes S5 can correspond to different frame rate adjustment ranges, such as different user modes S5 can correspond to different maximum frame rates and the same minimum frame rate FR; different user modes S5 can also correspond to different maximum frame rates and different minimum frame rates. For example:

[0086] The minimum frame rate of all user modes S5 is set to 30 minutes per frame, about 0.00056 FPS, the maximum frame rate of the energy-saving mode (S5=0) is set to 10 FPS, the maximum frame rate of the normal mode (S5=1) is set to 20 FPS, and the maximum frame rate of the motion mode (S5=2) is set to 30 FPS.

[0087] In specific embodiments, the maximum frame rate of each mode can also be dynamically adjusted based on the device state, such as according to the storage space of the device, the battery level of the device, etc., and the set maximum frame rate of the motion mode, the maximum frame rate of the normal mode, and the maximum frame rate of the energy-saving mode decrease in turn.

[0088] The frame rate adjustment range is the maximum frame rate corresponding to the user mode to the minimum frame rate corresponding to each user mode The maximum frame rate corresponding to each user mode does not exceed the maximum frame rate supported by the smart glasses , and the minimum frame rate corresponding to each user mode not less than the minimum frame rate supported by the smart glasses .

[0089] Based on the target priority, the adjusted target frame rate, i.e., the second frame rate, is calculated, and shooting is performed according to the second frame rate. The formula for calculating the second frame rate is as follows:

[0090] )

[0091] is the current frame rate of the wearable device or a preset reference frame rate (such as an average frame rate), P is the target priority, is a fixed parameter.

[0092] For example, after the user mode of the wearable device is obtained and the frame rate adjustment range of the shooting device in the user mode is determined, the method further includes:

[0093] If the second frame rate does not belong to the frame rate adjustment range, when the second frame rate is greater than the maximum frame rate in the frame rate adjustment range, the maximum frame rate is taken as the adjusted frame rate, and shooting is performed according to the maximum frame rate.

[0094] When the second frame rate is less than the minimum frame rate in the frame rate adjustment range, the minimum frame rate is taken as the adjusted frame rate, and shooting is performed according to the minimum frame rate.

[0095] In this embodiment, based on the second frame rate, the shooting frame rate of the smart glasses is dynamically changed within the frame rate adjustment range corresponding to the user mode, i.e., if the priority P is extremely low, the FR approaches the minimum frame rate (30 minutes per frame); if P is extremely high, the FR approaches the maximum frame rate in the current mode:

[0096] When the second frame rate is not less than the minimum frame rate in the current user mode and not greater than the maximum frame rate in the current user mode, shooting is performed based on the second frame rate;

[0097] When the second frame rate is less than the minimum frame rate in the current user mode, shooting is performed based on the minimum frame rate in the current user mode;

[0098] When the second frame rate is greater than the maximum frame rate in the current user mode, shooting is performed based on the maximum frame rate in the current user mode.

[0099] Further, before the current user mode of the wearable device is obtained, the method further includes:

[0100] Based on the user setting instruction, the device state parameter of the wearable device, and / or the scene change parameter, the user mode of the wearable device is set or updated.

[0101] In this embodiment, the user mode can be adaptively adjusted based on the scene change corresponding to the shooting scene. For example, if the scene change parameter is large, the current user mode is adjusted to the motion mode; if the scene change parameter is small, the current user mode is adjusted to the energy saving mode; if the scene change parameter reaches the average value, the current user mode is adjusted to the normal mode.

[0102] Upon receiving the user's mode setting instruction, the current user mode is adjusted or set based on the user's voice instruction or selection operation instruction in the device interface.

[0103] Upon detecting that the device state parameter of the smart glasses is abnormal (such as insufficient storage space or insufficient power), the current user mode is automatically adjusted to the energy saving mode.

[0104] Further, the shooting parameter includes a first resolution, and the step S40 includes:

[0105] Based on the target priority and the first resolution, a second resolution is calculated;

[0106] The resolution adjustment range of the shooting device is obtained;

[0107] If the second resolution belongs to the resolution adjustment range, the second resolution is taken as the adjusted resolution, and shooting is performed according to the second resolution.

[0108] The shooting parameter of the shooting device of the wearable device is adjusted according to the target priority, and shooting is performed according to the adjusted shooting parameter, including:

[0109] If the second resolution does not belong to the resolution adjustment range, when the second resolution is greater than the maximum resolution in the resolution adjustment range, the maximum resolution is taken as the adjusted resolution, and shooting is performed according to the maximum resolution.

[0110] When the second resolution is less than the minimum resolution in the resolution adjustment range, the minimum resolution is taken as the adjusted resolution, and shooting is performed according to the minimum resolution.

[0111] In this embodiment, the resolution is not affected by the user mode, and the resolution adjustment range is between the minimum resolution and the maximum resolution that can be supported by the shooting device.

[0112] Based on the second resolution, the shooting resolution of the smart glasses is dynamically changed within the resolution adjustment range (such as 360p to 4K), that is, when P is very high, the maximum resolution is selected for shooting; when P is very low, the minimum resolution is maintained for shooting, saving power consumption:

[0113] when the second resolution is not less than the minimum resolution and not greater than the maximum resolution, capturing based on the second resolution;

[0114] when the second resolution is less than the minimum resolution, capturing based on the minimum resolution;

[0115] when the second resolution is greater than the maximum resolution, capturing based on the maximum resolution.

[0116] It can be understood that if a subsequent key event (S4 is greatly increased) is identified through a low-frequency cycle, the frame rate or resolution is continuously increased in subsequent recording.

[0117] In the foregoing manner, the logarithm is removed, the priority is calculated through pure multiplicative calculation, the influence degree of the key event on the shooting parameter is flexibly regulated and controlled based on multiple dimensions. Further, through the limitation of the minimum frame rate, the resource waste caused by the continuous empty shooting of the shooting device of the wearable device is prevented, and the highest frame rate is further limited through the user mode, the compatibility of the wearable device for the sports scene and the long-time recording scene is improved. In addition, the user mode and the resolution are decoupled, the resolution is independently adjusted, and the accurate regulation and control of various shooting parameters are realized.

[0118] In combination with the foregoing embodiments, an embodiment is further provided to describe the shooting method applied to the wearable device:

[0119] 1. When the user is in a low-motion state of sitting and the event importance parameter corresponding to the wearable device is low (i.e., the energy-saving mode + low event importance), if S1=01, S2=01, S3=0~5, S4=2 (low score, indicating a non-key event), if =0.2, =0.3, =0.01, =0.5, and α=1.2, then P≈(1+0.2×1)×(1+0.3×1)×(1+0.01×5)×(1+0.5×21.2)≈19.

[0120] The P value is relatively low, the frame rate is relatively low (the minimum frame rate or slightly higher than the minimum frame rate), the resolution is relatively low (the minimum resolution or slightly higher than the minimum resolution), and the wearable device is in a low-power-consumption state.

[0121] 2. When the user is in a normal state of motion, such as walking down the street, and the wearable device corresponds to a moderate event importance parameter (i.e., moderate motion + moderate event importance in Normal mode), S1 = 45, S2 = 35, S3 = 20-30, and S4 = 40. Priority P increases significantly, reaching tens or even hundreds. The maximum frame rate in Normal mode is 20 FPS, but the actual frame rate is close to 20 FPS. At 720p or 1080p resolution, the wearable device can capture clearer images. Furthermore, as the event importance parameter S4 increases, α provides an additional amplification effect on the event importance parameter.

[0122] 3. When the user is in a high-intensity running state during a sporting event and the wearable device corresponds to high time importance parameters (i.e., sports mode + high event importance), S1 = 810, S2 = 59, S3 = 50-80, and multimodal model analysis shows S4 = 90, α = 1.5\alpha = 1.5, S4 significantly improves priority P. The frame rate easily reaches the sports mode upper limit of 30 FPS, and the resolution can be increased to near the device's maximum value, ensuring complete capture of intense motion and important events. The S4 analysis strategy is frequently executed in this state, reducing the risk of missing critical images (or key events) for a moment.

[0123] Among them, S1, S2, S3, and S4 are body movement amplitude data, eye movement amplitude data, the scene change parameter, and the event importance parameter, respectively. It is the exponential parameter of the event importance parameter, which is used to amplify or suppress the event importance exponentially.

[0124] Therefore, this application uses four major signals: body movement amplitude (S1), eye movement amplitude (S2), scene change (S3), and event importance (S4). Through a purely multiplicative priority formula and the introduction of exponent α in the S4 part, key events are exponentially amplified at high priorities, thereby achieving high-fidelity capture. In addition, in any user mode, the minimum frame rate is no less than one frame every 30 minutes, the normal mode is up to 20 FPS, and the sports mode is up to 30 FPS. The resolution is flexibly selected based on the priority P and the device support range, thus meeting the energy saving and clarity requirements in various usage scenarios.

[0125] See also Figure 4 , Figure 4 1 is a schematic block diagram of the structure of a wearable device provided in an embodiment of the present application. The computer device may be a server.

[0126] See Figure 4 The computer device includes a processor, a memory, and a network interface connected through a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0127] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions which, when executed, cause the processor to perform any one of the photographing methods.

[0128] The processor is configured to provide computing and control capabilities to support the operation of the entire computer device.

[0129] The internal memory provides an environment for the computer program in the non-volatile storage medium to run, and the computer program, when executed by the processor, causes the processor to perform any one of the photographing methods.

[0130] The network interface is configured to perform network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that, Figure 4 It should be understood that the structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0131] It should be understood that the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic components, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0132] In one embodiment, the processor is configured to run a computer program stored in the memory to perform the following steps:

[0133] Obtain a user motion parameter of the wearable device;

[0134] Obtain a scene change parameter of an environment in which the wearable device is located, and obtain an event importance parameter of the wearable device;

[0135] Calculate a target priority according to the user motion parameter, the scene change parameter, and the event importance parameter;

[0136] Adjust a photographing parameter of a photographing device of the wearable device according to the target priority, and perform photographing according to the adjusted photographing parameter.

[0137] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0138] calculating a second frame rate based on the target priority and the first frame rate;

[0139] obtaining a user mode of the wearable device, and determining a frame rate adjustment range of the photographing device in the user mode;

[0140] if the second frame rate belongs to the frame rate adjustment range, taking the second frame rate as an adjusted frame rate, and photographing according to the second frame rate.

[0141] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0142] if the second frame rate does not belong to the frame rate adjustment range, when the second frame rate is greater than a maximum frame rate in the frame rate adjustment range, taking the maximum frame rate as the adjusted frame rate, and photographing according to the maximum frame rate;

[0143] when the second frame rate is less than a minimum frame rate in the frame rate adjustment range, taking the minimum frame rate as the adjusted frame rate, and photographing according to the minimum frame rate.

[0144] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0145] setting or updating a user mode of the wearable device based on a user setting instruction, a device state parameter of the wearable device, and / or the scene change parameter.

[0146] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0147] calculating a second resolution based on the target priority and the first resolution;

[0148] obtaining a resolution adjustment range of the photographing device;

[0149] if the second resolution belongs to the resolution adjustment range, taking the second resolution as an adjusted resolution, and photographing according to the second resolution.

[0150] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0151] If the second resolution is not within the resolution adjustment range, when the second resolution is greater than a maximum resolution within the resolution adjustment range, the maximum resolution is taken as the adjusted resolution, and photographing is performed according to the maximum resolution.

[0152] When the second resolution is less than a minimum resolution within the resolution adjustment range, the minimum resolution is taken as the adjusted resolution, and photographing is performed according to the minimum resolution.

[0153] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0154] The event importance parameter is calculated based on a preset event scoring model, the user motion parameter, and the scene change parameter.

[0155] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0156] When the frame rate in the photographing parameter is lower than a minimum frame rate, key frames are extracted from photographing images of the wearable device based on a preset period to obtain a key frame set, and the event scoring model is trained based on the key frame set.

[0157] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0158] The event importance parameter is generated based on image semantics of photographing images of the wearable device.

[0159] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0160] A scene type of an environment in which the wearable device is located is obtained, and adjustment coefficients corresponding to the user motion parameter, the event importance parameter, and the scene change parameter are determined based on the scene type;

[0161] The target priority is calculated based on the adjustment coefficients, the user motion parameter, the event importance parameter, and the scene change parameter.

[0162] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0163] An index parameter of the event importance parameter is obtained, and the target priority is calculated based on the user motion parameter, the scene change parameter, the event importance parameter, and the index parameter.

[0164] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0165] acquire a parameter acquisition period corresponding to each of the user motion parameter, the scene change parameter and the event importance parameter;

[0166] acquire or update the user motion parameter, the scene change parameter and the event importance parameter respectively based on the parameter acquisition period.

[0167] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0168] The user motion parameter includes a user body motion amplitude parameter and a user eye movement amplitude parameter.

[0169] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the computer program includes program instructions. The processor executes the program instructions to implement any one of the photographing methods provided by the embodiments of the present application.

[0170] The computer readable storage medium can be an internal storage unit of the computer device, for example, a hard disk or a memory of the computer device. The computer readable storage medium can also be an external storage device of the computer device, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc.

[0171] The above merely illustrates the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A photographing method characterized by comprising: The photographing method is applied to a wearable device and comprises the following steps: obtaining a user motion parameter of the wearable device, wherein the user motion parameter comprises a user body motion amplitude parameter and a user eye movement amplitude parameter; obtaining a scene change parameter of an environment in which the wearable device is located and obtaining an event importance parameter of the wearable device, wherein the event importance parameter is a key event importance degree parameter corresponding to an image photographed by the wearable device; calculating a target priority according to the user motion parameter, the scene change parameter and the event importance parameter, wherein the higher the target priority, the higher the importance degree of the image photographed by the wearable device, and the target priority is calculated by a priority calculation formula, and the calculation formula of the priority P is: wherein, is a user body motion amplitude parameter, is a user eye movement amplitude parameter, 3 is a scene change parameter, is the event importance parameter, is , 2, 3, 4 is an adjustment parameter in priority calculation, is an exponential parameter of the event importance parameter, used to power up or suppress the event importance; adjusting a photographing parameter of a photographing device of the wearable device according to the target priority and photographing according to the adjusted photographing parameter; wherein the event importance parameter of the wearable device is obtained by: calculating the event importance parameter based on a preset event scoring model, the user motion parameter and the scene change parameter, wherein the more the combined sub-events in an event, the higher the level of the event, and the higher the level, the higher the score, and a key event is an event with a score higher than a threshold value; wherein the target priority is calculated according to the user motion parameter, the scene change parameter and the event importance parameter, comprising: obtaining a scene type of an environment in which the wearable device is located and determining an adjustment coefficient corresponding to the user motion parameter, the event importance parameter and the scene change parameter based on the scene type; calculating the target priority based on each adjustment coefficient, the user motion parameter, the event importance parameter and the scene change parameter.

2. The photographing method of claim 1, wherein The photographing parameter comprises a first frame rate, and the adjusting of the photographing parameter of the photographing device of the wearable device according to the target priority and the photographing according to the adjusted photographing parameter comprise: calculating a second frame rate based on the target priority and the first frame rate; obtaining a user mode of the wearable device and determining a frame rate adjustment range of the photographing device in the user mode; if the second frame rate belongs to the frame rate adjustment range, the second frame rate is taken as the adjusted frame rate, and photographing is performed according to the second frame rate.

3. The photographing method of claim 2, wherein After the obtaining of the user mode of the wearable device and the determination of the frame rate adjustment range of the photographing device in the user mode, the method further comprises: if the second frame rate does not belong to the frame rate adjustment range, when the second frame rate is greater than a maximum frame rate in the frame rate adjustment range, the maximum frame rate is taken as the adjusted frame rate, and photographing is performed according to the maximum frame rate; when the second frame rate is less than a minimum frame rate in the frame rate adjustment range, the minimum frame rate is taken as the adjusted frame rate, and photographing is performed according to the minimum frame rate.

4. The photographing method of claim 2, wherein, Before the obtaining of the current user mode of the wearable device, the method further comprises: The user mode of the wearable device is set or updated based on a user setting instruction, a device state parameter of the wearable device, and / or the scene change parameter.

5. The photographing method of claim 1, wherein The shooting parameter includes a first resolution, the adjusting the shooting parameter of the shooting device of the wearable device according to the target priority, and the shooting according to the adjusted shooting parameter, includes: calculating a second resolution based on the target priority and the first resolution; obtaining a resolution adjustment range of the shooting device; if the second resolution belongs to the resolution adjustment range, taking the second resolution as the adjusted resolution, and shooting according to the second resolution.

6. The photographing method of claim 5, wherein, The shooting parameter includes a first resolution, the adjusting the shooting parameter of the shooting device of the wearable device according to the target priority, and the shooting according to the adjusted shooting parameter, includes: if the second resolution does not belong to the resolution adjustment range, when the second resolution is greater than a maximum resolution in the resolution adjustment range, taking the maximum resolution as the adjusted resolution, and shooting according to the maximum resolution; when the second resolution is less than a minimum resolution in the resolution adjustment range, taking the minimum resolution as the adjusted resolution, and shooting according to the minimum resolution.

7. The shooting method according to claim 1, wherein: The calculating the event importance parameter based on the preset event scoring model, the user motion parameter, and the scene change parameter, includes: when a frame rate in the shooting parameter is lower than a minimum frame rate, extracting key frames from shooting images of the wearable device based on a preset period to obtain a key frame set, and training the event scoring model based on the key frame set.

8. The photographing method of claim 1, wherein, The obtaining the event importance parameter of the wearable device includes: generating the event importance parameter based on image semantics of the shooting images of the wearable device.

9. The photographing method of claim 1, wherein, The calculating the target priority according to the user motion parameter, the scene change parameter, and the event importance parameter, includes: obtaining an index parameter of the event importance parameter, and calculating the target priority based on the user motion parameter, the scene change parameter, the event importance parameter, and the index parameter.

10. The photographing method of claim 1, wherein, The shooting method further includes: obtaining parameter collection periods corresponding to the user motion parameter, the scene change parameter, and the event importance parameter, respectively; collecting or updating the user motion parameter, the scene change parameter, and the event importance parameter based on the respective parameter collection periods.

11. A wearable device, comprising: The wearable device includes a processor, a memory, and a shooting program stored on the memory and executable by the processor, wherein the shooting program, when executed by the processor, implements the steps of the shooting method according to any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a shooting program, wherein the shooting program, when executed by a processor, implements the steps of the shooting method according to any one of claims 1 to 10.

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