CN113138384A - Image acquisition method and device and storage medium - Google Patents
Image acquisition method and device and storage medium Download PDFInfo
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- CN113138384A CN113138384A CN202010054602.0A CN202010054602A CN113138384A CN 113138384 A CN113138384 A CN 113138384A CN 202010054602 A CN202010054602 A CN 202010054602A CN 113138384 A CN113138384 A CN 113138384A
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- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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Abstract
The disclosure relates to an image acquisition method and device and a storage medium. The method comprises the following steps: when the terminal equipment carries out image acquisition, transmitting radar waves and detecting first echoes of the radar waves; determining whether the current posture of the acquisition object is a set acquisition posture or not according to the first echo; and when the current posture is the set acquisition posture, acquiring an image of an acquisition object. Through the embodiment of the disclosure, images can be timely acquired when the acquisition object is well-posed, the condition that the existing time-delay photographing function performs photographing because the pose is not well-posed or the time delay time is not achieved when the pose is well-posed can be reduced, and the image acquisition is more intelligent.
Description
Technical Field
The present disclosure relates to the field of information processing technologies, and in particular, to an image acquisition method and apparatus, and a storage medium.
Background
With the improvement of living standard of people, terminal equipment such as mobile phones are widely used. The conventional terminal equipment usually has an image acquisition function, so that a user can record the daily life of the user by using the image acquisition function, and great convenience is brought to the life of people.
However, when the terminal device is used for image acquisition, it has always been paid much attention to how to enrich the image acquisition function to improve the acquisition experience.
Disclosure of Invention
The disclosure provides an image acquisition method and device and a storage medium.
According to a first aspect of the embodiments of the present disclosure, there is provided an image capturing method applied in a terminal device, the method including:
when the terminal equipment carries out image acquisition, transmitting radar waves and detecting first echoes of the radar waves;
determining whether the current posture of the acquisition object is a set acquisition posture or not according to the first echo;
and when the current posture is the set acquisition posture, acquiring an image of an acquisition object.
In some embodiments, the determining whether the current posture of the acquisition object is the set acquisition posture according to the first echo comprises:
and identifying whether the current posture of the acquisition object corresponding to the first echo is the set acquisition posture or not through a posture identification model.
In some embodiments, the method further comprises:
acquiring a second echo of the radar wave under the set acquisition posture;
and learning through a neural network by using the echo parameters of the second echo, and training to obtain the gesture recognition model.
In some embodiments, the method further comprises:
and outputting posture adjustment information when the current posture is not the set acquisition posture.
In some embodiments, the method further comprises:
and outputting posture reminding information when the image acquisition duration is detected to reach the preset duration.
In some embodiments, the image capturing the capture object when the current posture is the set capture posture comprises:
when the current posture is the set acquisition posture, determining an acquisition mode corresponding to the current posture;
and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current posture.
According to a second aspect of embodiments of the present disclosure, there is provided an image capturing apparatus, the apparatus comprising:
the transmitting module is configured to transmit radar waves and detect first echoes of the radar waves when the terminal equipment performs image acquisition;
the determining module is configured to determine whether the current posture of the acquisition object is a set acquisition posture or not according to the first echo;
and the acquisition module is configured to acquire an image of an acquisition object when the current posture is the set acquisition posture.
In some embodiments, the determining module is specifically configured to identify, by a gesture recognition model, whether the current gesture of the acquisition object corresponding to the first echo is the set acquisition gesture.
In some embodiments, the apparatus further comprises:
an acquisition module configured to acquire a second echo of the radar wave in the set acquisition posture;
and the training module is configured to learn through a neural network by using the echo parameters of the second echo, and train to obtain the gesture recognition model.
In some embodiments, the apparatus further comprises:
a first output module configured to output pose adjustment information when the current pose is not the set acquisition pose.
In some embodiments, the apparatus further comprises:
and the second output module is configured to output the posture reminding information when detecting that the image acquisition duration reaches the preset duration.
In some embodiments, the acquisition module is specifically configured to determine, when the current posture is the set acquisition posture, an acquisition mode corresponding to the current posture; and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current posture.
According to a third aspect of the embodiments of the present disclosure, there is provided an image capturing apparatus including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the image acquisition method as described in the first aspect above.
According to a fourth aspect of embodiments of the present disclosure, there is provided a storage medium including:
the instructions in said storage medium, when executed by a computer processor, enable the computer to perform the image acquisition method as described in the first aspect above.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
the disclosed embodiments determine whether the current posture is the set acquisition posture based on the first echo, and automatically perform image acquisition when the current posture is determined to be the set acquisition posture. Therefore, on one hand, the image can be automatically acquired when the acquisition object is ready to set the acquisition posture, the condition that the existing time-delay photographing function automatically executes photographing because the posture is not ready or the time delay time is not ready to execute automatic photographing because the posture is ready can be reduced, the image acquisition function is more intelligent, and the user experience is improved. On the other hand, because the radar waves can radiate farther distance and have strong anti-interference capability, whether the current posture is the set acquisition posture or not can be determined more accurately through the echo of the radar waves, the accuracy of posture identification is improved, and the probability of poor experience of the user who automatically acquires the images due to error identification can be reduced.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a flowchart of an image capturing method according to an embodiment of the present disclosure.
Fig. 2 is a flowchart of an image capturing method according to an embodiment of the present disclosure.
Fig. 3 is a flowchart of an image acquisition method shown in the embodiment of the present disclosure.
Fig. 4 is a flowchart of a fourth image acquisition method according to the embodiment of the present disclosure.
Fig. 5 is a flowchart of an image capturing method shown in the embodiment of the present disclosure.
Fig. 6 is a flowchart six illustrating an image capturing method according to an embodiment of the present disclosure.
Fig. 7 is a flowchart seven illustrating an image capturing method according to an embodiment of the present disclosure.
Fig. 8 is a first image acquisition device according to an embodiment of the present disclosure.
Fig. 9 is a second image capturing device shown in the embodiment of the present disclosure.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
Fig. 1 is a flowchart of a first image capturing method shown in the embodiment of the present disclosure, and as shown in fig. 1, the image capturing method applied to the terminal device includes the following steps:
s11, when the terminal equipment carries out image acquisition, transmitting radar waves and detecting first echoes of the radar waves;
s12, determining whether the current posture of the acquisition object is a set acquisition posture or not according to the first echo;
and S13, when the current posture is the set collection posture, collecting the image of the collection object.
Above-mentioned terminal equipment is for being provided with the terminal equipment of image acquisition module, and this terminal equipment can be wearable electronic equipment and mobile terminal, and this mobile terminal includes cell-phone, notebook and panel computer, and this wearable electronic equipment includes intelligent wrist-watch, and this disclosed embodiment does not do the restriction.
The image acquisition module is used for acquiring images based on ambient light. This image acquisition module includes: the rear camera with the collection surface facing the back shell of the terminal device and the front camera with the collection surface facing the screen of the terminal device are not limited in the embodiment of the disclosure.
The terminal equipment is also provided with a radar module. The radar module can comprise a radar transmitting component for transmitting radar waves and a radar receiving component for receiving echoes of the radar waves, wherein the radar waves are electromagnetic waves, and the speed of propagation in vacuum is the speed of light.
It should be noted that the number of the radar modules on the terminal device is at least one. When the radar module is set to be one, the orientation of the transmitting surface of the radar module can be changed through the rotating module in the terminal equipment. For example, when an image is collected based on the front camera, the emitting surface of the radar module can be driven to face the front camera so as to emit radar waves to a collection object within the view finding range of the front camera; when gathering the image based on rear camera, can drive radar module's transmitting surface towards rear camera to the collection object transmission radar wave in the scope of framing of rear camera.
As shown in fig. 2, the number of the radar modules 101 may be two. The two radar modules are arranged in the terminal equipment, and the transmitting surface of one radar module faces towards the arrangement direction of the front camera; the transmitting surface of the other radar module faces towards the setting direction of the rear camera. When the image is collected based on the front camera, triggering the radar module with the transmitting surface facing the front camera to transmit radar waves; when gathering the image based on rear camera, trigger the transmitting surface and face towards the radar module transmission radar wave of rear camera.
In the embodiment of the disclosure, when the image acquisition module of the terminal device acquires an image, the radar receiving assembly can receive a first echo of a radar wave reflected back by an acquired object.
It should be noted that the above-mentioned acquisition object is an object within the view range in the image acquisition module, and the acquisition object may be a human or an animal with posture change.
In the embodiment of the present disclosure, after receiving the first echo, it is necessary to determine whether the current posture of the acquisition object is the set acquisition posture according to the first echo.
In an embodiment of the present disclosure, the first echo may be used to determine whether a current posture of the acquisition object is a set acquisition posture. In the process of acquiring an image of an acquisition object, the position between the acquisition object and the terminal device is relatively static, and the acquisition object performs switching of different set acquisition postures at the position to acquire images and images corresponding to different postures. Therefore, the embodiment of the disclosure may determine the current posture of the acquisition object based on the first echo of the radar waves corresponding to different postures.
The first echo can also be used for determining the distance of the collected object by combining the radar waves transmitted by the radar module. It should be noted that the distance to the acquisition object may be determined based on the transmission time of the radar wave, the reception time of the first echo, and the propagation speed of the radar wave.
The first echo may also be based on a motion velocity of the object acquired during the doppler effect determination process of the radar wave propagation. The determining of the motion velocity of the acquisition object includes determining the motion velocity of the acquisition object based on a difference between a reception frequency of the first echo and a transmission frequency of the radar wave. It should be noted that, when the acquisition object moves toward the terminal device, the receiving frequency of the echo is greater than the transmitting frequency of the radar wave; when the collecting object moves towards the direction away from the terminal equipment, the receiving frequency of the echo is smaller than the transmitting frequency of the radar wave.
In this embodiment of the disclosure, according to the first echo, determining whether the current posture of the acquisition object is the set acquisition posture includes: whether the acquisition object is the set acquisition posture is determined based on the first echo and the posture recognition model, and the contour parameter of the acquisition object can be determined according to the first echo, so that whether the acquisition object is the set acquisition posture is determined based on the contour parameter.
Illustratively, the set acquisition gestures include, but are not limited to, various standing gestures, various wall-leaning gestures, various gestures that are implemented by means of objects such as windmills, balloons, or flowers, and so forth.
It should be noted that, when a terminal device such as a mobile phone is used to capture an image, if a delayed photographing function on the mobile phone is used, the mobile phone usually performs photographing at intervals of a preset delay time, and a user needs to make a capture gesture within the preset delay time. Because different people require different delay times and different delay times for converting different postures, photographing is performed based on the preset delay time, and therefore the photographing is performed when the posture is not done, or the photographing is performed after the posture is done and long time is needed.
Based on this, the embodiment of the present disclosure has found that the problem of poor user experience due to the time-delay based photographing is just mentioned, and it is proposed that whether the current pose is the set acquisition pose is determined based on the first echo of the radar module on the terminal device, and image acquisition is automatically performed when the current pose is the set acquisition pose. Therefore, on one hand, the image can be acquired in time when the acquisition object is ready to set the acquisition posture, the condition that the existing time-delay photographing function performs photographing because the posture is not ready or the time delay time is not up after the posture is ready can be reduced, the image acquisition function is more intelligent, and the user experience is improved; on the other hand, because the radar waves can radiate farther distance and have strong anti-interference capability, whether the current posture is the set acquisition posture or not can be determined more accurately through the echo of the radar waves, the accuracy of posture identification is improved, and the probability of poor experience of the user who automatically acquires the images due to error identification can be reduced.
In one embodiment, as shown in fig. 3, the determining whether the current posture of the acquisition object is the set acquisition posture according to the first echo, namely step S12, includes:
s12a, recognizing, by a gesture recognition model, whether the current gesture of the acquisition object corresponding to the first echo is the set acquisition gesture.
In the embodiment of the disclosure, the terminal device stores the gesture recognition model in advance, and after the first echo is acquired, the terminal device may recognize whether the current gesture is the set acquisition gesture based on the gesture recognition model, and further determine whether to perform image acquisition.
The posture recognition model may be configured by a plurality of posture recognition submodels that can recognize whether or not the current posture of the acquisition target corresponding to different echoes is the set acquisition posture.
In the embodiment of the disclosure, when the current posture of the acquisition object is determined to be the set acquisition posture, the acquisition object is shown to be already in a posture, and then the acquisition object in the current posture can be subjected to image acquisition; and when the current posture of the acquisition object is determined not to be the set acquisition posture, the acquisition object is in the acquisition posture adjustment process, and at the moment, the terminal equipment does not execute image acquisition.
Therefore, images can be acquired in time when the acquisition object is well-done in posture, the condition that the existing time-delay photographing function performs photographing or the time delay time is not reached when the posture is not well-done can be reduced, the image acquisition function is more intelligent, and the user experience is improved.
In one embodiment, as shown in fig. 4, the method further comprises:
s14, acquiring a second echo of the radar wave in the set acquisition posture;
and S15, learning through a neural network by using the echo parameters of the second echo, and training to obtain the gesture recognition model.
In the embodiment of the disclosure, before recognizing the current gesture through the gesture recognition model, the terminal device needs to acquire a second echo of a radar wave under a set acquisition gesture, and performs learning through a neural network by using an echo parameter of the second echo to obtain the gesture recognition model through training.
The echo parameters include, but are not limited to, echo frequency and/or echo amplitude. It should be noted that the echo amplitudes and/or frequencies of different echoes are different. When the current posture is a standing posture, the amplitude of the corresponding echo is a first amplitude; and when the current posture is the posture close to the wall, the amplitude of the corresponding echo is a second amplitude, and the first amplitude is different from the second amplitude. Thus, by determining whether the amplitude of the echo is the first amplitude or the second amplitude, it is possible to determine whether the current posture is a standing posture or a wall-leaning posture. Similarly, it may also be determined whether the current pose is the set acquisition pose based on the frequency of the echo. Thus, a gesture recognition model may be trained based on the echo parameters of the different echoes.
In the embodiment of the present disclosure, in the training process of training to obtain the gesture recognition model, the echo parameters of at least two second echoes are obtained under the preset acquisition gesture, and various data in the echo parameters are input into the neural network for learning, so as to generate the gesture recognition model for recognizing the set acquisition gesture. It should be noted that, in the learning process of the neural network, the same or similar echo parameters that can represent the preset acquisition posture are extracted from the echo parameters of the at least two second echoes by the neural network, and a posture recognition model for recognizing the posture is obtained based on the same or similar echo parameters.
Illustratively, the neural network includes, but is not limited to, a perceptron neural network or a Back Propagation (BP) neural network.
It should be noted that, in the embodiment of the present disclosure, performing gesture recognition on an input echo parameter by using a gesture recognition model obtained by training a perceptron neural network includes: inputting a second echo, and outputting the current posture of the acquisition object as a result of setting the acquisition posture by the posture recognition model when the echo parameter of the input second echo is the echo parameter corresponding to the preset acquisition posture; when the input parameters of the second echo do not belong to the echo parameters corresponding to the set acquisition posture, the posture recognition model outputs the result that the current posture of the acquisition object is not the set acquisition posture.
Therefore, the gesture recognition model is obtained through the training of the echo parameters of the second echo, whether the current gesture of the collected object is the set collection gesture or not can be recognized, the gesture recognition basis is provided for the follow-up timely image collection, the condition that the shooting is executed just because the gesture is not made or the shooting cannot be executed because the delay time is not made for the gesture in the existing delayed shooting function can be reduced, the image collection function is more intelligent, and the user experience is improved.
In some embodiments, the third echoes of all gestures in the image generated by the terminal device through the user operation are counted; the gesture recognition model is optimized based on the echo parameters of the third echo.
The image generated by the user operation includes: clicking an image acquisition icon by a user to enable the terminal equipment to acquire an image; or, the terminal device is enabled to acquire the image through user voice input. Therefore, in the process of subsequently using the terminal device to acquire images, the gesture recognition model can be optimized based on the images generated by the user operation, the recognition capability of the gesture recognition model can be improved, and the accuracy of executing image acquisition after automatically recognizing and setting the acquisition gesture is further improved.
In one embodiment, as shown in fig. 5, the method further comprises:
and S16, outputting posture adjustment information when the current posture is not the set collection posture.
According to the embodiment of the disclosure, when the current posture is the set acquisition posture, the terminal device acquires an image of an acquisition object; and when the current posture is not the set acquisition posture, the terminal equipment outputs the adjustment information. The output adjustment information is used to prompt the user to adjust the current pose.
It should be noted that the manner of outputting the adjustment information includes, but is not limited to, voice output or prompt box output; the outputting the adjustment information includes: and outputting character information or picture information of the acquisition posture to be adjusted.
The acquisition pose to be adjusted may be any set acquisition pose in a set acquisition pose library, or a set acquisition pose similar to the current pose, or a set acquisition pose similar to the current scene, which is not limited in the embodiments of the present disclosure.
The posture adjustment information is output, the user can be reminded to adjust the current posture in time, the user experience is improved, the posture adjustment information can be used for additionally providing the collection posture which can be used by the user, the situation that the user does not know which collection posture to adopt for image collection is reduced, and the image collection function is richer and more flexible.
In some embodiments, after outputting the pose adjustment information, determining to acquire an object adjusted pose;
and when the posture before the adjustment and the posture after the adjustment are the same in the preset time, triggering the terminal equipment to execute image acquisition.
The preset time may be set according to actual needs, for example, may be set to 30 seconds or 60 seconds, and the embodiment of the present disclosure is not limited.
It should be noted that, in the actual image acquisition process, due to the limitation of the gesture recognition model training samples or program execution errors, a situation that the gesture recognition model cannot recognize the current gesture or the current gesture recognition is incorrect may occur. Based on this, the embodiment of the present disclosure proposes to establish an error-proofing mechanism, and trigger the terminal device to perform image acquisition if the adjusted posture is the same as the posture before the adjustment within a preset time. Therefore, an error-proofing mechanism can be added for the terminal equipment, the situation that the gesture recognition model causes recognition errors or cannot be recognized is reduced, and the recognition effect of the gesture recognition model in the terminal equipment is improved.
In other embodiments, a fourth echo returned in response to the adjusted gesture is acquired, and the gesture recognition model is trained based on echo parameters of the fourth echo. In this way, the trained gesture recognition model can reduce the probability of erroneous recognition or recognition failure due to the same reason, and further improve the gesture recognition capability.
In some embodiments, the method further comprises:
and outputting posture reminding information when the image acquisition duration is detected to reach the preset duration.
In the embodiment of the present disclosure, the preset time period may be designed according to actual needs, for example, the preset time period may be set to 1 minute or 30 seconds, and the embodiment of the present disclosure is not limited.
The gesture reminding information can be used for reminding that the acquisition object is in image acquisition and needs to put out an acquisition gesture so as to realize automatic identification and image acquisition of the acquisition gesture; the method can be used for reminding the acquisition object of multiple acquisition gestures available for reference, so that the acquisition object selects one acquisition gesture from the multiple reference acquisition gestures to realize automatic identification and image acquisition of the acquisition gesture. The output mode of the gesture reminding information includes, but is not limited to, a voice output mode.
In the embodiment of the disclosure, posture reminding information is output through the image acquisition duration, so that a user can be reminded to timely put out an acquisition posture to finish image acquisition or put out what acquisition posture to finish image acquisition, the image acquisition is more intelligent, the user experience is improved, the condition that the user carries out image acquisition because the user does not know what acquisition posture to adopt can be reduced, and the image acquisition function is richer and more flexible.
In some embodiments, the image capturing the capture object when the current posture is the set capture posture comprises:
when the current posture is the set acquisition posture, determining an acquisition mode corresponding to the current posture;
and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current posture.
In the embodiment of the disclosure, a collection of collection postures is preset, each collection posture in the collection corresponds to one image collection mode, and when the current posture is any one set collection posture in the collection, the image collection mode corresponding to the set collection posture is determined.
It should be noted that the above-mentioned acquisition mode may include: a camera mode and a picture taking mode. When the acquisition mode corresponding to the current posture is a shooting mode, triggering a shooting function by the current posture of the acquisition object, so that the terminal equipment shoots the acquisition object; and when the acquisition mode corresponding to the current posture is a photographing mode, photographing the acquisition object in the current posture.
The capture modes may also include various scene capture modes including, but not limited to, a night scene capture mode, a sunset scene capture mode, and a black and white scene capture mode, for example.
Of course, the above-mentioned capture modes may also include other capture modes, such as a large-aperture photographing mode, a panoramic photographing mode, a macro photographing mode, and the like.
According to the embodiment of the disclosure, the image acquisition can be performed based on different acquisition modes through the current posture, so that the image acquisition mode is more flexible.
In one embodiment, the method further comprises:
determining whether an image acquisition mode of the terminal equipment is a gesture recognition mode;
when the terminal equipment carries out image acquisition, the method for transmitting radar waves and detecting the echoes of the radar waves comprises the following steps:
and when the terminal equipment is in the gesture recognition mode for image acquisition, transmitting the radar wave and detecting an echo of the radar wave.
The gesture recognition mode is different from a common acquisition mode of the terminal equipment, and is used for automatically executing image acquisition when the current gesture of the acquisition object is a preset acquisition gesture; while a general acquisition mode is used to perform image acquisition based on an operation of a user. Compared with the common acquisition mode, the gesture recognition mode automatically performs image acquisition and does not need user operation.
In the embodiment of the disclosure, a gesture recognition mode may be added in the image acquisition mode of the terminal device, and when it is determined that the image acquisition mode of the terminal device is the gesture recognition mode, the radar wave is emitted and the echo of the radar wave is detected.
It should be noted that the terminal device may add a gesture recognition capture icon on the preview interface of image capture, and enter the gesture recognition mode when the touch screen detects an input acting on the gesture recognition capture icon.
Therefore, the gesture recognition mode is triggered, so that the photographing can be automatically performed based on the gesture recognition without manually performing the photographing, the operation is more convenient, meanwhile, the image can be timely acquired when the object is acquired to be well-posed in a gesture, the existing delayed photographing function can be reduced, the photographing can be performed due to the fact that the gesture is not well done, or the situation that the photographing cannot be performed due to the fact that the delay time is not well done in the gesture is avoided, the image acquisition is more intelligent, and the user experience is improved.
In order to facilitate understanding of the embodiment of the present disclosure, a terminal device is used as a mobile phone, and the embodiment of the present disclosure further provides the following examples:
as shown in fig. 6, when image acquisition is performed, the acquisition target is switched from the first acquisition posture 21 to the second acquisition posture 22. And the radar module of the mobile phone transmits radar waves to the acquisition object under the second acquisition posture and receives echoes of the radar waves returned by the acquisition object under the second acquisition posture. And determining the second acquisition posture to be the set acquisition posture according to the echo of the radar wave returned by the acquisition object in the second acquisition posture, so that the mobile phone can perform image acquisition on the acquisition object in the second acquisition posture.
As shown in fig. 7, before determining whether the current posture of the acquisition object is the set acquisition posture, the mobile phone may first train to obtain a posture recognition model, and then determine whether to perform image acquisition based on the trained posture recognition model, specifically, the following steps are performed:
s101, acquiring a second echo of the radar wave under the set acquisition posture;
s102, learning through a neural network by using the echo parameters of the second echo, and training to obtain a gesture recognition model;
s103, determining whether an image acquisition mode of the terminal equipment is a gesture recognition mode;
s104, when the terminal equipment is in a gesture recognition mode for image acquisition, transmitting radar waves and detecting first echoes of the radar waves;
s105, identifying whether the current posture of the acquisition object corresponding to the first echo is a set acquisition posture or not through a posture identification model;
s106, when the current posture is the set acquisition posture, determining an acquisition mode corresponding to the current posture;
and S107, acquiring an image of the acquisition object based on the acquisition mode corresponding to the current posture.
It is understood that the embodiments of the present disclosure determine whether the current posture is the set acquisition posture based on the first echo, and automatically perform image acquisition when determining that the current posture is the set acquisition posture. Therefore, on one hand, the image can be automatically acquired when the acquisition object is ready to set the acquisition posture, the condition that the existing time-delay photographing function automatically executes photographing because the posture is not ready or the time delay time is not ready to execute automatic photographing because the posture is ready can be reduced, the image acquisition function is more intelligent, and the user experience is improved. On the other hand, because the radar waves can radiate farther distance and have strong anti-interference capability, whether the current posture is the set acquisition posture or not can be determined more accurately through the echo of the radar waves, the accuracy of posture identification is improved, and the probability of poor experience of the user who automatically acquires the images due to error identification can be reduced.
Fig. 8 is a diagram illustrating an image capture device i according to an exemplary embodiment. Referring to fig. 8, the image capturing apparatus includes a transmitting module 1001, a determining module 1002, and a capturing module 1003, wherein,
a transmitting module 1001 configured to transmit a radar wave and detect a first echo of the radar wave when the terminal device performs image acquisition;
a determining module 1002 configured to determine whether a current posture of the acquisition object is a set acquisition posture according to the first echo;
an acquiring module 1003 configured to acquire an image of an acquisition object when the current posture is the set acquisition posture.
In some embodiments, the determining module is specifically configured to identify, by a gesture recognition model, whether the current gesture of the acquisition object corresponding to the first echo is the set acquisition gesture.
In some embodiments, the apparatus further comprises:
an acquisition module configured to acquire a second echo of the radar wave in the set acquisition posture;
and the training module is configured to learn through a neural network by using the echo parameters of the second echo, and train to obtain the gesture recognition model.
In some embodiments, the apparatus further comprises:
a first output module configured to output pose adjustment information when the current pose is not the set acquisition pose.
In some embodiments, the apparatus further comprises:
and the second output module is configured to output the posture reminding information when detecting that the image acquisition duration reaches the preset duration.
In some embodiments, the acquisition module is specifically configured to determine, when the current posture is the set acquisition posture, an acquisition mode corresponding to the current posture; and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current posture.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
FIG. 9 illustrates an image capture device according to an exemplary embodiment. For example, the device may be a mobile phone, a mobile computer, etc.
Referring to fig. 9, an apparatus may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the device, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the device. Examples of such data include instructions for any application or method operating on the device, contact data, phonebook data, messages, pictures, videos, and the like. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The power component 806 provides power to various components of the device. The power components 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for a device.
The multimedia component 808 includes a screen that provides an output interface between the device and the user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the device is in an operational mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor component 814 includes one or more sensors for providing status assessment of various aspects of the device. For example, the sensor assembly 814 may detect the on/off status of the device, the relative positioning of the components, such as the display and keypad of the apparatus, the sensor assembly 814 may also detect a change in the position of the apparatus or a component of the apparatus, the presence or absence of user contact with the apparatus, the orientation or acceleration/deceleration of the apparatus, and a change in the temperature of the apparatus. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate wired or wireless communication between the apparatus and other devices. The device may access a wireless network based on a communication standard, such as Wi-Fi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the apparatus may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the apparatus to perform the method described above is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
A non-transitory computer readable storage medium in which instructions, when executed by a computer processor, enable a computer to perform a method of image acquisition, the method comprising:
when the terminal equipment carries out image acquisition, transmitting radar waves and detecting first echoes of the radar waves;
determining whether the current posture of the acquisition object is a set acquisition posture or not according to the first echo;
and when the current posture is the set acquisition posture, acquiring an image of an acquisition object.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (14)
1. An image acquisition method is applied to a terminal device, and the method comprises the following steps:
when the terminal equipment carries out image acquisition, transmitting radar waves and detecting first echoes of the radar waves;
determining whether the current posture of the acquisition object is a set acquisition posture or not according to the first echo;
and when the current posture is the set acquisition posture, acquiring an image of the acquisition object.
2. The method of claim 1, wherein determining whether a current pose of an acquisition object is a set acquisition pose according to the first echo comprises:
and identifying whether the current posture of the acquisition object corresponding to the first echo is the set acquisition posture or not through a posture identification model.
3. The method of claim 2, further comprising:
acquiring a second echo of the radar wave under the set acquisition posture;
and learning through a neural network by using the echo parameters of the second echo, and training to obtain the gesture recognition model.
4. The method according to any one of claims 1 to 3, further comprising:
and outputting posture adjustment information when the current posture is not the set acquisition posture.
5. The method according to any one of claims 1 to 3, further comprising:
and outputting posture reminding information when the image acquisition duration is detected to reach the preset duration.
6. The method according to any one of claims 1 to 3, wherein the image capturing an acquisition object when the current posture is the set acquisition posture comprises:
when the current posture is the set acquisition posture, determining an acquisition mode corresponding to the current posture;
and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current posture.
7. An image acquisition apparatus, characterized in that the apparatus comprises:
the transmitting module is configured to transmit radar waves and detect first echoes of the radar waves when image acquisition is carried out on the terminal equipment;
the determining module is configured to determine whether the current posture of the acquisition object is a set acquisition posture or not according to the first echo;
and the acquisition module is configured to acquire an image of the acquisition object when the current posture is the set acquisition posture.
8. The apparatus according to claim 7, wherein the determining module is specifically configured to identify, via a gesture recognition model, whether the current gesture of the acquisition object corresponding to the first echo is the set acquisition gesture.
9. The apparatus of claim 8, further comprising:
an acquisition module configured to acquire a second echo of the radar wave in the set acquisition posture;
and the training module is configured to learn through a neural network by using the echo parameters of the second echo, and train to obtain the gesture recognition model.
10. The apparatus of any one of claims 7 to 9, further comprising:
a first output module configured to output pose adjustment information when the current pose is not the set acquisition pose.
11. The apparatus of any one of claims 7 to 9, further comprising:
and the second output module is configured to output the posture reminding information when detecting that the image acquisition duration reaches the preset duration.
12. The apparatus according to any one of claims 7 to 9, wherein the acquisition module is specifically configured to determine, when the current posture is the set acquisition posture, an acquisition mode corresponding to the current posture; and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current posture.
13. An image acquisition apparatus, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the image acquisition method of any one of claims 1 to 6.
14. A non-transitory computer readable storage medium, wherein instructions in the storage medium, when executed by a processor, enable the processor to perform the image acquisition method of any of claims 1 to 6.
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