CN113138384B - Image acquisition method and device and storage medium - Google Patents
Image acquisition method and device and storage medium Download PDFInfo
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- CN113138384B CN113138384B CN202010054602.0A CN202010054602A CN113138384B CN 113138384 B CN113138384 B CN 113138384B CN 202010054602 A CN202010054602 A CN 202010054602A CN 113138384 B CN113138384 B CN 113138384B
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- 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
- G01S13/88—Radar or analogous systems specially adapted for specific applications
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
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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: transmitting radar waves and detecting first echoes of the radar waves when the terminal equipment performs image acquisition; determining whether the current gesture of the acquisition object is a set acquisition gesture according to the first echo; and when the current gesture is the set acquisition gesture, acquiring an image of an acquisition object. According to the embodiment of the disclosure, the image can be timely acquired when the gesture of the acquired object is made, the condition that the existing delay photographing function performs photographing because the gesture is not made or the delay time is not made can be reduced, and the image acquisition is more intelligent.
Description
Technical Field
The disclosure relates to the technical field of information processing, and in particular relates to an image acquisition method and device and a storage medium.
Background
With the improvement of living standard of people, terminal devices such as mobile phones have been widely used. The existing terminal equipment generally has an image acquisition function, so that a user can record own daily life by utilizing the image acquisition function, and great convenience is brought to life of people.
However, how to enrich the image capturing function to enhance the capturing experience is attracting attention in the use of terminal devices for image capturing.
Disclosure of Invention
The disclosure provides an image acquisition method and device and a storage medium.
According to a first aspect of embodiments of the present disclosure, there is provided an image acquisition method, applied to a terminal device, the method including:
transmitting radar waves and detecting first echoes of the radar waves when the terminal equipment performs image acquisition;
determining whether the current gesture of the acquisition object is a set acquisition gesture according to the first echo;
and when the current gesture is the set acquisition gesture, acquiring an image of an acquisition object.
In some embodiments, the determining whether the current pose of the acquisition object is a set acquisition pose according to the first echo comprises:
and identifying whether the current gesture of the acquisition object corresponding to the first echo is the set acquisition gesture or not through a gesture identification model.
In some embodiments, the method further comprises:
acquiring a second echo of the radar wave in the set acquisition posture;
and learning through a neural network by utilizing 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 time length is detected to reach the preset time length.
In some embodiments, the image capturing of the captured object when the current pose is the set capturing pose includes:
when the current gesture is the set acquisition gesture, determining an acquisition mode corresponding to the current gesture;
and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current gesture.
According to a second aspect of embodiments of the present disclosure, there is provided an image acquisition 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 gesture of the acquisition object is a set acquisition gesture according to the first echo;
and the acquisition module is configured to acquire images of the acquisition object when the current gesture is the set acquisition gesture.
In some embodiments, the determining module is specifically configured to identify, through 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 utilizing the echo parameters of the second echo, and train to obtain the gesture recognition model.
In some embodiments, the apparatus further comprises:
and the first output module is configured to output posture adjustment information when the current posture is not the set acquisition posture.
In some embodiments, the apparatus further comprises:
and the second output module is configured to output gesture reminding information when the image acquisition time length is detected to reach the preset time length.
In some embodiments, the acquisition module is specifically configured to determine an acquisition mode corresponding to the current gesture when the current gesture is the set acquisition gesture; and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current gesture.
According to a third aspect of 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 comprising:
the instructions in the 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 comprise the following beneficial effects:
the disclosed embodiments determine whether the current pose is a set acquisition pose based on the first echo and automatically perform image acquisition when the current pose is determined to be the set acquisition pose. So, on the one hand, the embodiment of the disclosure can automatically collect images when the collection object makes the setting of the collection gesture, can reduce the situations that the existing delay photographing function automatically executes photographing because the gesture is not made or the delay time is not enough for executing automatic photographing because the gesture is made, so that the image collection function is more intelligent, and the user experience is improved. On the other hand, as the radar wave can radiate a longer distance and has strong anti-interference capability, whether the current gesture is a set acquisition gesture can be more accurately determined through the echo of the radar wave, the accuracy of gesture recognition is improved, and the probability of poor user experience of automatically acquiring images due to false recognition can be further 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 application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart of an image capturing method according to an embodiment of the present disclosure.
Fig. 2 is a flowchart second of an image acquisition method according to an embodiment of the disclosure.
Fig. 3 is a flowchart three of an image acquisition method according to an embodiment of the present disclosure.
Fig. 4 is a flowchart of an image capturing method according to an embodiment of the present disclosure.
Fig. 5 is a flowchart five of an image acquisition method according to an embodiment of the present disclosure.
Fig. 6 is a flowchart six of an image capturing method according to an embodiment of the present disclosure.
Fig. 7 is a flowchart seven of an image capturing method according to an embodiment of the present disclosure.
Fig. 8 is a diagram of an image capturing device according to an embodiment of the present disclosure.
Fig. 9 is a second image capturing device diagram according to an embodiment of the present disclosure.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
Fig. 1 is a flowchart of an image capturing method according to an embodiment of the present disclosure, and as shown in fig. 1, the image capturing method applied to a terminal device includes the following steps:
s11, transmitting radar waves and detecting first echoes of the radar waves when the terminal equipment performs image acquisition;
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 gesture is the set acquisition gesture, acquiring an image of an acquisition object.
The terminal device is a terminal device provided with an image acquisition module, and the terminal device can be a wearable electronic device and a mobile terminal, wherein the mobile terminal comprises a mobile phone, a notebook and a tablet personal computer, and the wearable electronic device comprises an intelligent watch.
The image acquisition module is used for acquiring images based on ambient light. The image acquisition module includes: the embodiment of the disclosure is not limited by the rear camera with the collection face facing the back shell of the terminal device and the front camera with the collection face facing the screen of the terminal device.
The terminal equipment is also provided with a radar module. The radar module may include a radar transmitting assembly for transmitting a radar wave and a radar receiving assembly for receiving an echo of the radar wave, wherein the radar wave is an electromagnetic wave and the speed of propagation in vacuum is a speed of light.
The number of the radar modules on the terminal equipment is at least one. When the radar module is set as one, the orientation of the emitting surface of the radar module can be changed by the rotating module in the terminal device. For example, when an image is acquired based on the front camera, the transmitting surface of the radar module may be driven to face the front camera to transmit a radar wave to an acquisition object within the view range of the front camera; when the image is acquired based on the rear camera, the transmitting surface of the radar module can be driven to face the rear camera so as to transmit radar waves to an acquisition object in the view-finding range of the rear camera.
As shown in fig. 2, the radar module 101 may be provided in two. The two radar modules are arranged in the terminal equipment, and the transmitting surface of one radar module faces the arrangement direction of the front camera; the transmitting surface of the other radar module faces the setting direction of the rear camera. When an image is acquired based on the front-facing camera, triggering the radar module with the transmitting surface facing the front-facing camera to transmit radar waves; when an image is acquired based on the rear camera, the radar module with the transmitting surface facing to the rear camera is triggered to transmit radar waves.
In the embodiment of the disclosure, when the image acquisition module of the terminal equipment performs image acquisition, the first echo of the radar wave reflected by the acquired object can be received through the radar receiving assembly.
It should be noted that, the above-mentioned object to be collected is an object in the view-finding range in the image collecting module, and the object to be collected may be a person or an animal with a posture change.
In the embodiment of the present disclosure, after receiving the first echo, it is required 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 disclosure, the first echo may be used to determine whether the current pose of the acquisition object is a set acquisition pose. In the process of image acquisition of the acquisition object, the position between the acquisition object and the terminal equipment is relatively static, and the acquisition object is switched in different setting acquisition postures at the position so as to acquire images and images corresponding to different postures. Accordingly, the embodiments of the present disclosure may determine the current pose of the acquisition object based on the first echoes of the radar waves corresponding to the different poses.
The first echo can also be used for determining the distance of the acquisition object by combining the radar wave emitted by the radar module. 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 used to determine the motion velocity of the acquisition object during the process based on the doppler effect of the radar wave propagation. The determining the motion speed of the acquisition object includes determining the motion speed of the acquisition object based on a difference between a reception frequency of the first echo and a transmission frequency of the radar wave. When the acquisition object moves towards the terminal device, the receiving frequency of the echo is larger than the transmitting frequency of the radar wave; when the acquisition object moves in a direction away from the terminal device, the reception frequency of the echo is smaller than the transmission frequency of the radar wave.
In an embodiment of the present disclosure, determining whether the current posture of the acquisition object is the set acquisition posture according to the first echo includes: based on the first echo and the gesture recognition model, whether the acquisition object is set to acquire a gesture is determined, and a profile parameter of the acquisition object can be determined according to the first echo, so that whether the acquisition object is set to acquire the gesture is determined based on the profile parameter.
Illustratively, the set acquisition positions include, but are not limited to, various standing positions, various wall positions, various positions implemented by means of objects such as windmills, balloons, flowers and plants, and the like.
It should be noted that, when the terminal device such as the mobile phone is used to collect the image, if the time-delay photographing function on the mobile phone is used, photographing is usually performed by the mobile phone at intervals of a preset time delay, and the user needs to make a collection gesture within the preset time delay. Because the delay time required by different people is different, the delay time required by converting different postures is also different, so that photographing is performed based on the preset delay time, and the photographing is performed when the postures are not done, or the photographing can be performed after the postures are done, which requires a long time.
Based on this, the embodiment of the disclosure finds the problem of poor user experience existing in the photographing based on the delay time, and proposes to determine whether the current gesture is the set acquisition gesture based on the first echo of the radar module on the terminal device, and automatically perform image acquisition when the current gesture is the set acquisition gesture. Thus, on one hand, the embodiment of the disclosure can timely acquire images when the acquisition object makes a set acquisition gesture, can reduce the situation that the existing delay photographing function performs photographing as long as the gesture is not made or the delay time is not reached when the gesture is made, so that the image acquisition function is more intelligent, and the user experience is improved; on the other hand, as the radar wave can radiate a longer distance and has strong anti-interference capability, whether the current gesture is a set acquisition gesture can be more accurately determined through the echo of the radar wave, the accuracy of gesture recognition is improved, and the probability of poor user experience of automatically acquiring images due to false recognition can be further reduced.
In one embodiment, as shown in fig. 3, the determining, according to the first echo, whether the current pose of the acquisition object is the set acquisition pose, i.e. step S12, includes:
s12a, recognizing whether the current gesture of the acquisition object corresponding to the first echo is the set acquisition gesture or not through a gesture recognition model.
In the embodiment of the disclosure, the terminal device stores the gesture recognition model in advance, and after acquiring the first echo, the terminal device may recognize whether the current gesture is a set acquisition gesture based on the gesture recognition model, thereby determining whether to perform image acquisition.
The gesture recognition model may be configured of a plurality of gesture recognition sub-models capable of recognizing whether or not the current gesture of the acquisition object corresponding to the different echoes is the set acquisition gesture.
In the embodiment of the disclosure, when the current gesture of the acquisition object is determined to be the set acquisition gesture, the acquisition object is indicated to have made a gesture, and then image acquisition can be performed on the acquisition object in the current gesture; when the current gesture of the acquisition object is determined not to be the set acquisition gesture, the acquisition object is indicated to be in the acquisition gesture adjusting process, and at the moment, the terminal equipment does not execute image acquisition.
Therefore, the image can be timely acquired when the acquired object takes the gesture, the condition that the existing delay photographing function performs photographing because the gesture is not taken or the delay time is not taken because the gesture is taken 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 utilizing the echo parameters of the second echo, and training to obtain the gesture recognition model.
In the embodiment of the disclosure, before the terminal device recognizes the current gesture through the gesture recognition model, the terminal device needs to acquire a second echo of the radar wave under the set acquisition gesture, learn through a neural network and train to obtain the gesture recognition model by using echo parameters of the second echo.
The echo parameters include, but are not limited to, the frequency of the echo and/or the echo amplitude. The echo amplitude and/or frequency of the different echoes are different. When the current posture is a standing posture, the amplitude of the corresponding echo is a first amplitude; when the current posture is a wall-leaning posture, the amplitude of the corresponding echo is a second amplitude, and the first amplitude and the second amplitude are different. 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 the standing posture or the wall-leaning posture. Similarly, it is also possible to determine whether the current posture is the set acquisition posture based on the frequency of the echo. Thus, a gesture recognition model may be trained based on echo parameters of different echoes.
In the embodiment of the disclosure, the training process of training to obtain the gesture recognition model may be to obtain echo parameters of at least two second echoes under the preset acquisition gesture, and input various data in the echo parameters 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 neural network may extract the same or similar echo parameters belonging to the echo parameters capable of representing the preset acquisition gesture from the echo parameters of the at least two second echoes, and train to obtain the gesture recognition model for recognizing the gesture based on the same or similar echo parameters.
Illustratively, the neural network includes, but is not limited to, a perceptron neural network or an error back propagation (BackPropagation, BP) neural network.
It should be noted that, in the embodiment of the present disclosure, gesture recognition is performed on the input echo parameters by using a gesture recognition model obtained by training a sensor neural network, including: inputting a second echo, and outputting a result of setting the current gesture of the acquisition object as the acquisition gesture by the gesture recognition model when the echo parameter of the input second echo is the echo parameter corresponding to the preset acquisition gesture; when the input parameters of the second echo do not belong to the echo parameters corresponding to the set acquisition gesture, the gesture recognition model outputs the result that the current gesture of the acquisition object is not the set acquisition gesture.
Therefore, the gesture recognition model is obtained by training the echo parameters of the second echo, whether the current gesture of the acquisition object is the set acquisition gesture can be recognized, a basis for recognizing the gesture is provided for the subsequent timely acquisition of the image, the situation that the existing delay photographing function can perform photographing because the gesture is not done well or the delay time of the gesture is not done well can be reduced, the image acquisition function is more intelligent, and the user experience is improved.
In some embodiments, counting third echoes of all gestures in the image generated by the terminal device through user operation; and optimizing the gesture recognition model based on the echo parameters of the third echo.
The image generated by the user operation includes: the user clicks the image acquisition icon to enable the terminal equipment to acquire the image; or, the image collected by the terminal equipment is input through the voice of the user. In this way, in the process of acquiring images by using the terminal equipment subsequently, the embodiment of the disclosure can optimize the gesture recognition model based on the images generated by user operation, so that the recognition capability of the gesture recognition model can be improved, and further, 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:
s16, outputting posture adjustment information when the current posture is not the set acquisition posture.
In the embodiment of the disclosure, when the current gesture is a set acquisition gesture, the terminal equipment acquires an image of an acquisition object; and the terminal equipment outputs the adjustment information when the current gesture is not the set acquisition gesture. The output adjustment information is used to prompt the user to adjust the current gesture.
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 output adjustment information includes: and outputting text information or picture information of the acquisition posture to be adjusted.
The collection gesture to be adjusted may be any collection gesture set in the collection gesture library, may be a collection gesture set close to the current gesture, or may be a collection gesture set close to the current scene, and the embodiment of the disclosure is not limited.
According to the embodiment of the disclosure, the gesture adjustment information is output, so that a user can be reminded of timely adjusting the current gesture, the user experience is improved, the gesture acquisition device can be used for additionally providing the acquisition gesture which can be used by the user, the situation that the user does not know what acquisition gesture is adopted for image acquisition is reduced, and the image acquisition function is richer and more flexible.
In some embodiments, after outputting the pose adjustment information, determining to acquire the subject adjusted pose;
and triggering the terminal equipment to execute image acquisition when the posture before adjustment and the posture after adjustment are the same in preset time.
The preset time may be set according to actual needs, for example, may be set to 30 seconds or 60 seconds, and embodiments of the present disclosure are not limited.
In the actual image acquisition process, the situation that the gesture recognition model cannot recognize the current gesture or the current gesture recognition is wrong may occur due to the limited training samples of the gesture recognition model or the wrong program execution. Based on this, the embodiment of the disclosure proposes to establish an error prevention mechanism, and trigger the terminal device to perform image acquisition if the adjusted posture and the posture before adjustment are the same in a preset time. Therefore, an error prevention 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, the adjusted pose corresponds to a fourth echo returned and the pose 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 incorrect recognition or incapability of recognition caused by the same reasons, and further improve the gesture recognition capability.
In some embodiments, the method further comprises:
and outputting posture reminding information when the image acquisition time length is detected to reach the preset time length.
In the embodiment of the present disclosure, the preset duration may be designed according to actual needs, for example, the preset duration may be set to 1 minute or 30 seconds, which is not limited in the embodiment of the present disclosure.
The gesture reminding information can be used for reminding that the acquisition object is in the image acquisition process, and the acquisition gesture needs to be put out to realize automatic identification and image acquisition of the acquisition gesture; the method can also be used for reminding the acquisition object of a plurality of acquisition postures which can be used for reference, so that the acquisition object can select one acquisition posture from the plurality of acquisition postures which can be used for reference, and the automatic identification and image acquisition of the acquisition posture can be realized. The output mode of the gesture reminding information includes, but is not limited to, a voice output mode.
In the embodiment of the disclosure, the gesture reminding information is output through the image acquisition time length, so that a user can be reminded of timely setting out the acquisition gesture to complete image acquisition or setting out what acquisition gesture to complete image acquisition, the image acquisition is more intelligent, the user experience is improved, the situation that the user does not know what acquisition gesture is adopted to conduct image acquisition can be reduced, and the image acquisition function is richer and more flexible.
In some embodiments, the image capturing of the captured object when the current pose is the set capturing pose includes:
when the current gesture is the set acquisition gesture, determining an acquisition mode corresponding to the current gesture;
and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current gesture.
In the embodiment of the disclosure, a collection gesture set is preset, each collection gesture in the set corresponds to an image collection mode, and when the current gesture is any set collection gesture in the set, the image collection mode corresponding to the set collection gesture is determined.
It should be noted that, the above acquisition modes may include: an image capturing mode and a photographing mode. When the acquisition mode corresponding to the current gesture is an image pickup mode, triggering an image pickup function according to the current gesture of the acquisition object, so that the terminal equipment picks up the image of the acquisition object; and when the acquisition mode corresponding to the current gesture is a photographing mode, photographing the acquisition object in the current gesture.
The acquisition modes described above may also include various scene acquisition modes including, for example, but not limited to, a night scene photographing mode, a sunset scene photographing mode, and a black and white scene photographing mode.
Of course, the above-mentioned acquisition modes may also include other acquisition 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 pose, 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;
transmitting radar waves and detecting echoes of the radar waves when the terminal equipment performs image acquisition, wherein the method comprises the following steps:
and when the terminal equipment is in the gesture recognition mode for image acquisition, transmitting the radar wave and detecting the echo of the radar wave.
The gesture recognition mode is different from a common acquisition mode of the terminal device, and is used for automatically executing image acquisition when the current gesture of the acquisition object is a preset acquisition gesture; whereas the normal acquisition mode is used to perform image acquisition based on the user's operation. The gesture recognition mode automatically performs image acquisition with respect to the normal acquisition mode, and does not require a user operation.
In the embodiment of the disclosure, a gesture recognition mode may be newly added in the image acquisition mode of the terminal device, and when the image acquisition mode of the terminal device is determined to be the gesture recognition mode, a radar wave is transmitted and an echo of the radar wave is detected.
It should be noted that, the terminal device may add a gesture recognition acquisition icon on the preview interface of image acquisition, and enter the gesture recognition mode when the touch screen detects an input acting on the gesture recognition acquisition icon.
Thus, the embodiment of the disclosure can automatically execute photographing based on gesture recognition by triggering the gesture recognition mode, and does not need to manually execute photographing, so that the operation is more convenient, and meanwhile, the embodiment of the disclosure can timely acquire images when an acquisition object makes a gesture, so that the condition that the existing delay photographing function can execute photographing without the gesture or the delay time of the gesture is not enough can be reduced, the image acquisition is more intelligent, and the user experience is improved.
In order to facilitate understanding of the embodiments of the present disclosure, with a terminal device as a mobile phone, the embodiments of the present disclosure further provide the following examples:
as shown in fig. 6, when image acquisition is performed, the acquisition object is switched from the first acquisition posture 21 to the second acquisition posture 22. The radar module of the mobile phone transmits radar waves to the acquisition object in the second acquisition posture and receives echoes of the radar waves returned by the acquisition object in the second acquisition posture. And determining the second acquisition posture as a set acquisition posture according to the echo of the radar wave returned by the acquisition object in the second acquisition posture, and further, 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 gesture of the object to be acquired is the set acquisition gesture, the mobile phone may be trained to obtain a gesture recognition model, and then determine whether to perform image acquisition based on the gesture recognition model obtained by training, which specifically includes the following implementation steps:
s101, acquiring a second echo of the radar wave under a set acquisition posture;
s102, learning through a neural network by utilizing 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, transmitting radar waves and detecting first echoes of the radar waves when the terminal equipment is in a gesture recognition mode for image acquisition;
s105, recognizing whether the current gesture of the acquisition object corresponding to the first echo is a set acquisition gesture or not through a gesture recognition model;
s106, when the current gesture is a set acquisition gesture, determining an acquisition mode corresponding to the current gesture;
and S107, performing image acquisition on the acquisition object based on an acquisition mode corresponding to the current gesture.
It is to be appreciated that embodiments of the present disclosure determine whether the current pose is a set acquisition pose based on the first echo and automatically perform image acquisition upon determining that the current pose is the set acquisition pose. So, on the one hand, the embodiment of the disclosure can automatically collect images when the collection object makes the setting of the collection gesture, can reduce the situations that the existing delay photographing function automatically executes photographing because the gesture is not made well or the delay time is not made by the gesture, so that the image collection function is more intelligent, and the user experience is improved. On the other hand, as the radar wave can radiate a longer distance and has strong anti-interference capability, whether the current gesture is a set acquisition gesture can be more accurately determined through the echo of the radar wave, the accuracy of gesture recognition is improved, and the probability of poor user experience of automatically acquiring images due to false recognition can be further reduced.
Fig. 8 is a diagram of an image capture device according to an exemplary embodiment. Referring to fig. 8, the image acquisition apparatus includes a transmission module 1001, a determination module 1002, and an acquisition 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, according to the first echo, whether a current posture of the acquisition object is a set acquisition posture;
and an acquisition 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, through 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 utilizing the echo parameters of the second echo, and train to obtain the gesture recognition model.
In some embodiments, the apparatus further comprises:
and the first output module is configured to output posture adjustment information when the current posture is not the set acquisition posture.
In some embodiments, the apparatus further comprises:
and the second output module is configured to output gesture reminding information when the image acquisition time length is detected to reach the preset time length.
In some embodiments, the acquisition module is specifically configured to determine an acquisition mode corresponding to the current gesture when the current gesture is the set acquisition gesture; and acquiring an image of the acquisition object based on the acquisition mode corresponding to the current gesture.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
Fig. 9 is a diagram of a second image capture device, according to an example embodiment. For example, the device may be a mobile phone, a mobile computer, etc.
Referring to fig. 9, the apparatus may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, a sensor component 814, and a 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 component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interactions 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 nonvolatile 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 disk.
The power component 806 provides power to the 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 devices.
The multimedia component 808 includes a screen between the device and the user that provides an output interface. 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 input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and/or a rear 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 focal length and optical zoom capabilities.
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 device is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 further 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 a keyboard, click wheel, buttons, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.
The sensor assembly 814 includes one or more sensors for providing status assessment of various aspects of the device. For example, the sensor assembly 814 may detect an on/off state of the device, a relative positioning of the assemblies, such as a display and keypad of the device, the sensor assembly 814 may also detect a change in position of the device or one of the assemblies of the device, the presence or absence of user contact with the device, a change in device orientation or acceleration/deceleration, and a change in temperature of the device. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects 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 gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communication between the apparatus and other devices in a wired or wireless manner. The device may access a wireless network based on a communication standard, such as Wi-Fi,2G, or 3G, or a combination thereof. In one exemplary embodiment, the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In one 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, microcontrollers, microprocessors, or other electronic elements for executing the methods described above.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 804 including instructions executable by processor 820 of the apparatus to perform the above-described method. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
A non-transitory computer readable storage medium, which when executed by a computer processor, causes a computer to perform an image acquisition method, the method comprising:
transmitting radar waves and detecting first echoes of the radar waves when the terminal equipment performs image acquisition;
determining whether the current gesture of the acquisition object is a set acquisition gesture according to the first echo;
and when the current gesture is the set acquisition gesture, acquiring an image of an acquisition object.
Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It is to be understood that the application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (10)
1. An image acquisition method, which is characterized by being applied to a terminal device, comprises the following steps: transmitting radar waves and detecting first echoes of the radar waves when the terminal equipment performs image acquisition;
determining whether the current gesture of the acquisition object is a set acquisition gesture according to the first echo;
when the current gesture is the set acquisition gesture, determining an acquisition mode corresponding to the current gesture based on an acquisition mode corresponding to the set acquisition gesture; each set acquisition gesture corresponds to an acquisition mode, and the acquisition modes comprise a shooting mode and a photographing mode;
image acquisition is carried out on the acquisition object based on the acquisition mode corresponding to the current gesture;
outputting posture adjustment information when the current posture is not the set acquisition posture;
after outputting the posture adjustment information, determining the posture of the object after the adjustment;
triggering the terminal equipment to execute image acquisition in response to the terminal equipment being in a gesture recognition mode and the gesture before adjustment and the gesture after adjustment being the same gesture within a preset time; the gesture recognition mode is a mode entered when input acting on a gesture recognition acquisition icon is detected through a touch screen, and is used for automatically executing image acquisition when the current gesture of an acquisition object is a set acquisition gesture.
2. The method of claim 1, wherein determining whether the current pose of the acquisition object is a set acquisition pose based on the first echo comprises:
and identifying whether the current gesture of the acquisition object corresponding to the first echo is the set acquisition gesture or not through a gesture identification model.
3. The method according to claim 2, wherein the method further comprises:
acquiring a second echo of the radar wave in the set acquisition posture;
and learning through a neural network by utilizing the echo parameters of the second echo, and training to obtain the gesture recognition model.
4. A method according to any one of claims 1 to 3, further comprising:
and outputting posture reminding information when the image acquisition time length is detected to reach the preset time length.
5. An image acquisition device, the device 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 gesture of the acquisition object is a set acquisition gesture according to the first echo;
the acquisition module is configured to determine an acquisition mode corresponding to the current gesture based on the acquisition mode corresponding to the set acquisition gesture when the current gesture is the set acquisition gesture; each set acquisition gesture corresponds to an acquisition mode, and the acquisition modes comprise a shooting mode and a photographing mode; when the current gesture is the set acquisition gesture, image acquisition is carried out on the acquisition object; outputting posture adjustment information when the current posture is not the set acquisition posture; after outputting the posture adjustment information, determining the posture of the object after the adjustment; triggering the terminal equipment to execute image acquisition in response to the terminal equipment being in a gesture recognition mode and the gesture before adjustment and the gesture after adjustment being the same gesture within a preset time; the gesture recognition mode is a mode entered when input acting on a gesture recognition acquisition icon is detected through a touch screen, and is used for automatically executing image acquisition when the current gesture of an acquisition object is a set acquisition gesture.
6. The apparatus of claim 5, 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.
7. The apparatus of claim 6, wherein 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 utilizing the echo parameters of the second echo, and train to obtain the gesture recognition model.
8. The apparatus according to any one of claims 5 to 7, further comprising:
and the second output module is configured to output gesture reminding information when the image acquisition time length is detected to reach the preset time length.
9. An image acquisition device, 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 4.
10. 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 one of claims 1 to 4.
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