WO2019218111A1

WO2019218111A1 - Electronic device and photographing control method

Info

Publication number: WO2019218111A1
Application number: PCT/CN2018/086692
Authority: WO
Inventors: 王星泽
Original assignee: 合刃科技（武汉）有限公司
Priority date: 2018-05-14
Filing date: 2018-05-14
Publication date: 2019-11-21
Also published as: CN111279682A

Abstract

The present application provides a photographing control method. The photographing control method comprises: during view-finding in photographing, acquiring view-finding information about a photographed object by means of a view-finding information acquisition unit; receiving the view-finding information, acquired by the view-finding information acquisition unit, about the photographed object, analyzing the view-finding information about the photographed object, so as to obtain an analysis result; and when it is determined according to the analysis result that a photographing condition is satisfied, controlling to execute a photographing operation and performing imaging processing at least by means of the first image processor, so as to obtain a corresponding photograph or video. The present application further provides an electronic device using said photographing control method. The photographing control method and the electronic device of the present application can use the view-finding information, which is acquired by the view-finding information acquisition unit and independent of the first image processor, about the photographed object to determine whether the photographing condition is satisfied currently, can automatically determine the timing for photographing, and captures wonderful moments in time, thereby avoiding waste of processing resources, and reducing power consumption.

Description

Electronic device and shooting control method

Technical field

The present application relates to the field of electronic devices, and in particular, to an electronic device having a photographing function and a photographing control method for the electronic device.

Background technique

Now, with the improvement of people's living standards, taking pictures has become a common function that is not indispensable in life. Nowadays, whether it is a camera or an electronic device such as a mobile phone or a tablet computer with a camera function, pixels are getting higher and higher, and the quality of photographs is getting better and better. However, current electronic devices such as cameras and mobile phones often require the user to initiate a photograph by pressing a shutter button or a photographing icon when performing photographing control. Since the user's operation often has a certain lag, it is often impossible to capture the wonderful time in time. In an instant, it is often impossible to take a satisfactory photo, or because of the lag, it has taken an unsatisfactory photo. For example, the subject may be in good condition when framing, but the moment when the photo is taken may appear that the eyes are not open, the smile is relatively stiff, and the final photographs are often unsatisfactory. For example, when taking pictures of a baby, the cute expression of the baby is often fleeting, and it is difficult to take a satisfactory photo in time by the user operating the shutter button or shooting an icon.

Summary of the invention

The application provides an electronic device and a shooting control method, which can perform a shooting operation in time according to the framing information, and capture a wonderful moment.

In one aspect, a photographing control method is provided, the photographing control method comprising: acquiring a framing information of a subject by a framing information acquiring unit when photographing a framing; and receiving a framing of the subject acquired by the framing information acquiring unit And analyzing the framing information of the subject to obtain an analysis result; and when determining that the shooting condition is satisfied according to the analysis result, controlling to perform a shooting operation to perform at least an imaging process by the first image processor to obtain a corresponding photo or video.

In another aspect, an electronic device is provided, the electronic device including a view information acquisition unit, a first image processor, and a processor. The framing information acquisition unit is configured to acquire framing information of the subject when the framing is taken. The first image processor is configured to perform an imaging process. The processor is configured to receive the framing information of the object acquired by the finder information acquiring unit, analyze the framing information of the object to obtain an analysis result, and control to perform a shooting operation when determining that the shooting condition is satisfied according to the analysis result At least an imaging process is performed by the first image processor to obtain a corresponding photo or video.

In still another aspect, a computer readable storage medium is provided, the computer readable storage medium storing program instructions, the program instructions being executed by a computer to execute a shooting control method, the shooting control method comprising: shooting At the time of framing, acquiring framing information of the subject by the framing information acquiring unit; receiving framing information of the subject acquired by the framing information acquiring unit, analyzing the framing information of the subject to obtain an analysis result; As a result, when it is determined that the photographing condition is satisfied, control is performed to perform a photographing operation to at least perform imaging processing by the first image processor to obtain a corresponding photograph or video.

The photographing control method and the electronic device of the present application can determine whether the photographing condition is currently satisfied by the framing information of the subject acquired by the framing information acquiring unit, and can automatically determine the timing of the photographing, and capture the exciting moment in time. At the same time, after obtaining the framing information independently of the framing information acquiring unit other than the first image processor, determining that the shooting condition is satisfied, the image processing is performed by the first image processor to obtain a corresponding photo or video. It avoids the waste of processing resources and further saves energy.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings to be used in the embodiments will be briefly described below. Obviously, the drawings in the following description are only some embodiments of the present application, Those skilled in the art can also obtain other obvious modifications according to these drawings without any creative work.

1 is a block diagram showing a schematic partial configuration of an electronic device in a first embodiment of the present application.

2 is a block diagram showing a schematic partial structure of an electronic device in a second embodiment of the present application.

3 is a block diagram showing a schematic partial structure of an electronic device in a third embodiment of the present application.

4 is a block diagram showing a schematic partial structure of an electronic device in a fourth embodiment of the present application.

FIG. 5 is a flowchart of a photographing control method in the first embodiment of the present application.

FIG. 6 is a flowchart of a photographing control method in a second embodiment of the present application.

FIG. 7 is a flowchart of a photographing control method in a third embodiment of the present application.

FIG. 8 is a flowchart of a photographing control method in a fourth embodiment of the present application.

FIG. 9 is a flowchart of a photographing control method in a fifth embodiment of the present application.

FIG. 10 is a flowchart of a photographing control method in a sixth embodiment of the present application.

FIG. 11 is a flowchart of a photographing control method in a seventh embodiment of the present application.

FIG. 12 is a flowchart of a photographing control method in an eighth embodiment of the present application.

FIG. 13 is a flowchart of a photographing control method in a ninth embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application are clearly and completely described in the following with reference to the drawings in the embodiments of the present application. It is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope are the scope of the present application.

Please refer to FIG. 1 , which is a block diagram showing a partial structure of an electronic device 100 in a first embodiment of the present application. As shown in FIG. 1 , the electronic device 100 includes a framing information acquiring unit 10 , an image processor 20 , and a processor 30 .

The finder information acquiring unit 10 is configured to acquire framing information of the subject when the framing is taken.

The image processor 20 is used to perform an imaging process.

The processor 30 is configured to receive the framing information of the subject acquired by the finder information acquiring unit 10, analyze the framing information of the subject, and obtain an analysis result, and determine, when the imaging condition is met according to the analysis result, the control is executed. The photographing operation is performed at least by the image processor 20 to obtain a corresponding photograph or video.

Therefore, in the present application, the framing information of the subject acquired by the finder information acquiring unit 10 can determine whether the shooting condition is currently satisfied, and can automatically determine the timing of the photographing, and capture the exciting moment in time. At the same time, after the framing information acquisition unit 10, which is independent of the image processor 20, performs the framing information acquisition, and determines that the shooting condition is satisfied, the image processing is performed by the image processor 20 to obtain a corresponding photo or video. It avoids the waste of processing resources and further saves energy.

In some embodiments, the photographic framing is performed in response to a framing operation.

Optionally, the processor 30 controls to perform shooting framing when receiving the shooting framing operation, and starts the framing information acquiring unit 10, so that the framing information acquiring unit 10 acquires framing information of the captured object. Therefore, the framing information acquiring unit 10 can be in a closed state at ordinary times to reduce power consumption of the power source.

In some embodiments, the shooting framing operation is a click operation on a photo application icon.

In other embodiments, the shooting framing operation is a specific operation of a physical button of the electronic device. For example, the electronic device includes a volume increasing button and a volume reducing button, and the shooting framing operation is a volume increasing button and a volume reduction. Simultaneous pressing of small keys. Further, the shooting framing operation is an operation of sequentially pressing the volume increasing key and the volume reducing key within a preset time (for example, 2 seconds).

In other embodiments, the shooting framing operation may also be an operation of a preset touch gesture input in any display interface of the electronic device, for example, on the main interface of the electronic device, the user may input a ring touch The touch gesture of the trajectory turns on the photographing function to perform framing.

In still other embodiments, the shooting framing operation may also be an operation of a preset touch gesture input on the touch screen when the electronic device is in a black screen state.

In some embodiments, when the electronic device is a camera, the shooting framing operation is an operation of pressing a shutter button/power button of the camera to trigger the camera to be in an activated state.

In some embodiments, the processor 30 analyzes the framing information of the subject to obtain an analysis result, and specifically includes: analyzing the framing information of the subject by using a preset model to obtain an analysis result.

Therefore, through the model analysis, the corresponding analysis result can be quickly obtained, and the shooting condition can be determined quickly according to the analysis result.

Please refer to FIG. 2, which is a block diagram showing a schematic partial structure of the electronic device 100 in the second embodiment. As shown in FIG. 2 , in another embodiment, the finder information acquiring unit 10 includes a depth sensor 11 , and the framing information is specifically obtained by the depth sensor 11 .

That is, the depth sensor 11 is used to acquire depth information of a subject when shooting a framing. That is, the depth information is the aforementioned framing information. The processor analyzes the framing information of the object by using a preset model to obtain an analysis result, including: receiving depth information of the object, and analyzing the depth information by using a preset model to obtain the Analysis results.

In some embodiments, the depth information includes spatial geometric distribution information of the subject.

For example, when the subject includes a face, the depth information will include spatial geometric distribution information of the face. When the subject includes a person's hand, the depth information will include spatial geometrical distribution information of the hand. When the subject includes a scene, the depth information will include spatial geometric distribution information of the scene.

In some embodiments, when the framing information obtained by the depth sensor 11 is analyzed by using a preset model, the preset model is operated to determine that the change/distribution of the spatial geometric position of the face is close to the reference expression to be captured, and An analysis result whose similarity is greater than a preset threshold is obtained.

The processor 30 determines that the shooting condition is currently satisfied when the analysis result whose similarity is greater than the preset threshold is obtained.

The depth sensor 11 is independent of the image sensor 20, and the power consumption is small, and the processing speed is faster. The depth information acquired by the depth sensor 11 determines whether to take a photo, which can effectively save energy and can be quickly The acquisition of the framing information ensures that the analysis results are obtained in time, and the shooting operation is performed in time when it is determined that the shooting conditions are met.

As shown in FIG. 2 , the electronic device 100 further includes a first lens 21 and a second lens 22 . The first lens 21 is disposed corresponding to the image sensor 20, and the image sensor is configured to perform imaging processing by receiving light through the first lens 21. Optionally, the first lens 21 and the image sensor 20 may be combined into a first camera module 201.

The second lens 22 is disposed corresponding to the depth sensor 11, and the depth sensor 11 is configured to acquire the finder information of the object by receiving the light through the second lens 22.

The first lens 21 and the second lens 22 can form a pseudo-camera structure on the appearance of the electronic device 100.

The first lens 21 and the second lens 22 may be disposed on the front surface of the electronic device 100 as a front imaging lens, or may be disposed on the back surface of the electronic device 100 as a rear imaging lens. The shooting operation in the present application may be a front shooting operation or a rear shooting operation.

Please refer to FIG. 3, which is a block diagram showing a schematic partial structure of the electronic device 100 in the third embodiment. The difference between the third embodiment and the second embodiment is that the second lens 22 can be cancelled, and the image sensor 20 and the depth sensor 11 can be disposed corresponding to the first lens 21, and the same is shared. The first lens 21 receives light.

In some embodiments, the depth sensor 11 is disposed side by side with the image sensor 20 and is disposed to the first lens 21, and the area of the depth sensor 11 facing the first lens 21 is smaller than the The image sensor 20 faces the area of the first lens 21, thereby minimizing the impact on the imaging of the image sensor 20. For example, the projected area of the depth sensor 11 on the first lens 21 is 1/3, 1/4, etc. of the projected area of the image sensor 20 on the first lens 21, as long as a small amount of light comes in to obtain the View information can be.

In other embodiments, the image sensor 20 is disposed opposite to the first lens 21, and a half mirror is disposed obliquely between the image sensor 20 and the first lens 21, and the depth sensor 11 is The light from the first lens 21 can be received on the light path of the reflective light of the half mirror.

Similarly, the first lens 21 can be disposed on the front or back of the electronic device 100.

In other embodiments, the depth sensor may not require a lens, that is, the first lens 21 is only disposed corresponding to the image sensor 20, and the depth sensor does not need a lens, but collects depth information by itself.

The foregoing depth sensor 11 may include at least one of a Stereo System depth sensor, a Structured Light depth sensor, and a Time Of Flight (TOF) depth sensor. Among them, the Stereo System depth sensor is an object that uses a dual camera to capture an object, and then calculates depth information such as object distance information by a triangle principle. The structured light sensor collects specific light information onto the surface of the object through the structured light, and then collects the depth information such as the object distance information by the camera. The time-of-flight depth sensor continuously transmits the light pulse to the target object, then receives the light returned from the object with the sensor, and obtains the target object distance by detecting the flight (round-trip) time of the light pulse, that is, according to the change of the optical signal caused by the object. Information such as the position and depth of the object, thereby restoring the entire three-dimensional space. Preferably, the depth sensor 11 comprises two of the above three depth sensors, for example, the depth sensor 11 comprises a binocular ranging depth sensor and a structured light depth sensor, that is, adding a structured light technology based on the binocular ranging technology, To combine the advantages of two depth sensors.

Please refer to FIG. 4, which is a block diagram showing a schematic partial structure of the electronic device 100 in the fourth embodiment. In the fourth embodiment, the finder information acquiring unit 10 includes an image sensor 12.

The image sensor 12 is configured to acquire image information of a subject in response to a shooting framing operation. That is, in the fourth embodiment, the image information is the aforementioned framing information.

The processor 30 is configured to receive the image information, and analyze the image information by using a preset model to obtain the analysis result.

As in the second embodiment, in the fourth embodiment, the electronic device 100 also includes a first lens 21 and a second lens 22.

The first lens 21 is disposed corresponding to the image sensor 20, and the image sensor is configured to perform imaging processing by receiving light through the first lens 21. Optionally, the first lens 21 and the image sensor 20 may be combined into a first camera module 201.

The second lens 22 is disposed corresponding to the image sensor 12, and the image sensor 12 is configured to acquire image information of a subject by receiving light through the second lens 22. In some embodiments, the second lens 22 and the image sensor 12 can be combined into a second camera module 202.

The first camera module 201 and the second camera module 202 may constitute a dual camera structure.

In some embodiments, the processor 30 determines that the shooting condition is controlled according to the analysis result, and the corresponding photo or video is obtained for controlling the imaging process by the image processor 20 and the image sensor 12 simultaneously. .

Thus, the image sensor 12 also participates in the imaging process of the final photo or video, which can effectively improve the shooting quality.

Obviously, in some embodiments, the image sensor 12 is only used to acquire image information for the preset model analysis to derive the analysis result, and does not participate in the imaging process.

In some embodiments, the resolution of the second camera module 202 combined with the image sensor 12 may be significantly smaller than the first combination of the first lens 21 and the image sensor 20 Camera module 201. For example, the resolution of the second camera module 202 is 30 W pixels, and the resolution of the first camera module 201 is 2000 W pixels. Correspondingly, the imaging resolution of the image sensor 12 for acquiring the framing information is also significantly smaller than the imaging resolution of the image sensor 20.

Therefore, when the image information is acquired by the second camera module 202, the image information only needs to satisfy the analysis result, and the resolution of the second camera module 202 and the image are The imaging resolution of the sensor 20 is set lower, saving processing resources and reducing power consumption.

In other embodiments, the second lens 22 can also be cancelled. The image sensor 20 and the image sensor 12 can be disposed corresponding to the first lens 21, and the first lens 21 is shared to receive light. .

In some embodiments, the image sensor 12 is disposed side by side with the image sensor 20 and is disposed to the first lens 21, and the area of the image sensor 12 facing the first lens 21 is smaller than the The image sensor 20 faces the area of the first lens 21, thereby minimizing the impact on the imaging of the image sensor 20. For example, the projected area of the image sensor 12 on the first lens 21 is 1/3, 1/4, etc. of the projected area of the image sensor 20 on the first lens 21, as long as a small amount of light comes in to obtain the View information can be. The processor 30 can also be used to perform the following operations. The electronic device 100 on which the following operations are based may be the electronic device 100 described in any of the aforementioned FIGS. 1 to 4.

In some embodiments, the preset model is a neural network model; the processor 30 analyzes the framing information of the subject by using a preset model to obtain an analysis result, including: the processor passes a neural network model The framing information of the subject is analyzed to obtain the analysis result of the satisfaction.

The processor 30 determines that the shooting condition is met according to the analysis result, and the processor 30 determines that the shooting condition is currently satisfied when determining that the satisfaction exceeds the satisfaction preset threshold.

In other embodiments, the preset model is an image processing algorithm model, and the processor 30 analyzes the framing information of the subject by using a preset model to obtain an analysis result, including: the processor 30 adopts The image processing algorithm model compares the framing information of the subject with the reference picture, and analyzes the analysis result of the similarity between the framing information of the subject and the reference picture.

The processor 30 determines that the shooting condition is currently satisfied according to the analysis result, and the processor 30 determines that the shooting condition is currently satisfied when determining that the similarity exceeds the similarity preset threshold. The similarity preset threshold may be 80%, 90%, and the like.

Optionally, the image processing algorithm model includes an expression feature model. When the object includes a human face, the processor 30 compares the framing information of the object with the reference image by using an image processing algorithm model, and analyzes The analysis result of the similarity between the framing information of the photographic subject and the reference picture includes: analyzing the facial expression information in the framing information of the captured object by using the face recognition technology to generate a corresponding expression feature vector; The expression feature vector corresponding to the framing information of the subject is calculated to obtain the similarity between the framing information and the reference picture.

In some embodiments, the expression feature model may include an expression feature vector corresponding to a plurality of reference pictures, and the plurality of similarities are determined by comparing the similarity between the expression feature vector corresponding to the view information and the expression feature vector of each reference picture. degree.

Further, when the plurality of reference pictures are included, the processor 30 determines that the similarity with any of the reference pictures exceeds the similarity preset threshold, and determines that the shooting condition is currently satisfied.

The reference picture corresponding to the expression feature model may be a standard picture including a specific expression such as a face laughing, sadness, anger, yawning, and the like.

Optionally, the image processing algorithm model includes a gesture feature model, and when the object to be photographed includes a human hand, the processor 30 compares the framing information of the object with the reference image by using an image processing algorithm model, and analyzes The analysis result of the similarity between the framing information of the object and the reference picture includes: analyzing the gesture information in the framing information of the object by using the image recognition technology to generate a corresponding gesture feature vector; according to the gesture feature model and The gesture feature vector corresponding to the framing information of the subject is calculated to obtain the similarity between the framing information of the subject and the reference picture.

In some embodiments, the gesture feature model may include a gesture feature vector corresponding to the plurality of reference pictures, and the plurality of similarities are determined by comparing the similarity between the expression feature vector corresponding to the view information and the gesture feature vector of each of the reference pictures. degree.

The reference picture corresponding to the gesture feature model may be a standard picture including a specific gesture such as an “OK” gesture, a “vertical thumb” gesture, a “V-shaped” gesture, and the like.

In some embodiments, the image processing algorithm model includes a scene feature model. When the object includes a scene, the processor uses an image processing algorithm model to compare the framing information of the object with the reference image, and analyzes the The analysis result of the similarity between the framing information of the photographic subject and the reference picture includes: using image recognition technology to analyze the scene information in the framing information of the object to generate a corresponding scene feature vector; according to the scene feature model and being photographed The scene feature vector corresponding to the framing information of the object calculates the similarity between the framing information of the subject and the reference picture.

In some embodiments, the scene feature model may include a scene feature vector corresponding to the plurality of reference pictures, and the plurality of similarities are determined by comparing the similarity between the scene feature vector corresponding to the finder information and the scene feature vector of each of the reference pictures. degree.

Further, when the plurality of reference pictures are included, the processor 30 determines that the similarity between the framing information and any of the reference pictures exceeds the similarity preset threshold, that is, determines the scene feature vector corresponding to the framing information When the similarity determined by the scene feature vector of the reference picture exceeds the similarity preset threshold, it is determined that the shooting condition is currently satisfied.

The reference picture corresponding to the scene feature model may be a standard picture including scenes such as “waves”, “mountains”, and “flowers”.

When the foregoing framing information is depth information, the feature vector such as the corresponding expression feature vector may be a three-dimensional vector. When the framing information is image information, the feature vector such as the corresponding expression feature vector may be a two-dimensional vector.

In some embodiments, the processor 30 controls to perform a photographing operation, including: the processor 30 controls to perform a continuous shooting operation to obtain a plurality of photos of the current subject.

In some embodiments, the processor 30 is further configured to analyze a plurality of photos acquired by the continuous shooting operation to determine an optimal photo; and retain the optimal photo for the connection The other photos obtained by the shooting operation are deleted.

In some embodiments, the processor 30 controls to perform a photographing operation, including: controlling to perform a video capture operation to obtain a currently captured video.

In some embodiments, the processor 30 is further configured to compare a plurality of video picture frames in the captured video to determine an optimal picture frame; and intercept the optimal picture frame. Save as a photo.

As shown in FIG. 1-4, the electronic device 100 further includes a memory 40, and the processor 30 retains the best photo or intercepts the best picture frame to save as a photo to control the most A good photo or the frame of the picture is saved in a certain preset album in the memory.

In some embodiments, the processor 30 is further configured to acquire satisfaction feedback information that the user feeds back a photo or video obtained by the shooting operation, and output the satisfaction feedback information to the preset model, so that The preset model performs optimization training using the satisfaction feedback information.

The preset model described above is a trained model or an untrained model. Using the satisfaction feedback information, when the model has been trained, further optimization can be performed, and when the model has not been trained, the training can be better achieved.

In some embodiments, program instructions are stored in the memory 40, and the processor 30 performs the aforementioned functions/operations for invoking program instructions stored in the memory 40. In other embodiments, program instructions are solidified in the processor 30, and the processor 30 performs the aforementioned functions/operations for calling its own program instructions.

The processor 30 can be a microcontroller, a microprocessor, a single chip, a digital signal processor, or the like. The memory 40 can be any storage device that can store information such as a memory card, a solid state memory, a micro hard disk, an optical disk, or the like.

The electronic device 100 can be a portable electronic device having a camera 30, such as a mobile phone, a tablet computer, a notebook computer, or the like, or a camera device such as a camera or a video camera.

As shown in FIG. 1, the electronic device 100 may further include an input and output unit 50 for inputting by a user and providing an output of a signal such as a display signal, a sound signal, and the like. In some embodiments, the input output unit 50 can include a touch screen while providing touch input and display output. Optionally, the input/output unit 50 may further include a power button, a physical button such as a volume button, a sound output device such as a speaker, and the like.

The program instruction stored in the memory 40 is further executed by the processor 30 to execute the shooting control method described in any of the following embodiments of FIG. 5 to FIG. The operation performed by the processor 30 may further refer to the introduction of the shooting control method in any of the following embodiments of FIG. 5 to FIG.

Please refer to FIG. 5 , which is a flowchart of a shooting control method in the first embodiment of the present application. The photographing control method is applied to the electronic device shown in any of the foregoing embodiments. The method includes the following steps:

S51: When performing the framing, the framing information acquiring unit acquires the framing information of the subject.

In some embodiments, the shooting framing is performed in response to the shooting framing operation, and the step S51 may specifically include: controlling the shooting framing in response to the shooting framing operation, and starting the framing information acquiring unit to acquire the framing of the subject. information. Therefore, the framing information acquiring unit can be started only when shooting and framing, and can be turned off normally to reduce energy consumption.

In some embodiments, the operation of capturing the framing is a click operation on the photo application icon.

In other embodiments, the shooting framing operation is a specific operation on a physical button of the electronic device, for example, the electronic device includes a volume increasing button and a volume reducing button, and the shooting framing operation is a volume increasing button and a volume. Reduce the pressing operation of the key while pressing. Further, the operation of capturing the framing is an operation of sequentially pressing the volume up key and the volume down key within a preset time (for example, 2 seconds).

In other embodiments, the shooting framing operation may also be an operation of a preset touch gesture input in any display interface of the electronic device, for example, on the main interface of the electronic device, the user may input a ring touch The touch gesture of the trajectory turns on the photographing function and starts shooting framing.

S53: Receive the framing information of the subject acquired by the framing information acquiring unit, and analyze the framing information of the subject to obtain an analysis result.

In some embodiments, the analyzing the framing information of the subject to obtain an analysis result comprises: analyzing the framing information of the subject by using a preset model to obtain an analysis result.

S55: When it is determined according to the analysis result that the shooting condition is satisfied, controlling to perform a shooting operation to perform imaging processing at least by the first image processor of the electronic device to obtain a corresponding photo or video.

In some embodiments, the controlling to perform a photographing operation comprises: controlling to perform a photographing operation, and at least performing an imaging process by the first image processor of the electronic device to obtain a photograph corresponding to the subject currently being photographed.

In some embodiments, the controlling to perform a photographing operation includes: controlling to perform a continuous shooting operation, and performing imaging processing by at least a first image processor of the electronic device to obtain a plurality of photographs of a current subject.

In some embodiments, the photographing control method further comprises: analyzing a plurality of photos acquired by the continuous shooting operation to determine an optimal photo; and retaining the optimal photo, and The other photos obtained by the shooting operation are deleted.

In still other embodiments, the controlling to perform a photographing operation includes: controlling to perform a video photographing operation, and at least performing an imaging process by the first image processor of the electronic device to obtain a video of a current subject.

In some embodiments, the photographing control method further comprises: comparing a plurality of video picture frames in the captured video to determine an optimal picture frame; and extracting the optimal picture frame. Save as a photo.

Please refer to FIG. 6 , which is a flowchart of a shooting control method in a second embodiment of the present application. In the second embodiment, the finder information acquiring unit includes a depth sensor, and the framing information is specifically obtained by the depth sensor. The method includes the following steps:

S61: When performing the framing, the depth information of the subject is acquired by the depth sensor.

In some embodiments, the depth information includes spatial geometric distribution information of the subject

S63: Receive depth information of the object acquired by the depth sensor, and analyze the depth information of the object by using a preset model to obtain an analysis result.

S65: When it is determined according to the analysis result that the shooting condition is satisfied, controlling to perform a shooting operation to perform imaging processing at least by the first image processor of the electronic device to obtain a corresponding photo or video.

In some embodiments, when the subject includes a human face, the step S63 may include: calculating the depth information by using the preset model, and determining that a change in a spatial geometric position of the face is close to a reference expression to be captured. At the same time, an analysis result whose similarity is greater than a preset threshold is obtained. The determining that the shooting condition is satisfied according to the analysis result may include: determining that the shooting condition is currently satisfied when the analysis result whose similarity is greater than the preset threshold is obtained.

Therefore, the depth sensor is independent of the image sensor 20, and the power consumption is small, the processing speed is faster, and the depth information acquired by the depth sensor determines whether to take a picture, which can effectively save energy and can quickly perform framing. The acquisition of information ensures that the analysis results are obtained in a timely manner, and the shooting operation is performed in time when it is determined that the shooting conditions are met.

The steps S61 to S65 correspond to the steps S51 to S55 in FIG. 5 respectively, and are the same or the relationship of the upper and lower positions, and the specific description can refer to each other.

Please refer to FIG. 7 , which is a flowchart of a shooting control method in a third embodiment of the present application. In the third embodiment, the framing information acquiring unit includes a second image sensor, and the framing information is specifically image information obtained by the second image sensor. The method includes the following steps:

S71: When performing the shooting framing, the image information of the subject is acquired by the second image sensor.

S73: Receive image information of the object acquired by the second image sensor, and analyze the depth information of the object by using a preset model to obtain an analysis result.

S75: When it is determined according to the analysis result that the shooting condition is satisfied, controlling to perform a shooting operation to perform imaging processing at least by the first image processor of the electronic device to obtain a corresponding photo or video.

Optionally, in an implementation manner, the controlling performs a photographing operation to obtain a corresponding photo or video by performing at least an imaging process by the first image processor of the electronic device, including: controlling simultaneously through the first The image processor and the second image sensor perform imaging processing to obtain a corresponding photo or video.

Thereby, the imaging process is simultaneously performed by the first image processor and the second image processor to achieve the effect of the dual camera imaging, and the imaging quality is improved.

Optionally, in another implementation manner, the controlling performs a photographing operation to obtain an image or a video according to at least an image processing performed by a first image processor of the electronic device, including: passing only the electronic device The first image processor performs imaging processing to obtain a corresponding photo or video.

Optionally, in some embodiments, an imaging resolution of the first image processor for acquiring the framing information is also significantly smaller than an imaging resolution of the image sensor, where the first image processor acquires The image information only needs to satisfy the analysis result to be accurate, and the imaging resolution of the first image processor is set lower, which can save processing resources and reduce energy consumption.

The step S71 corresponds to the step S51 in FIG. 5 . For a specific description, refer to the related description of step S51 in FIG. 5 . Steps S73 and S75 respectively correspond to steps S53 and S55 in FIG. 5, which are steps of the same or upper and lower positions, and specific descriptions can be referred to each other.

Please refer to FIG. 8 , which is a flowchart of a shooting control method in a fourth embodiment of the present application. In the fourth embodiment, the preset model is specifically a neural network model, and the shooting control method includes the following steps:

S81: When shooting the framing, the framing information acquiring unit acquires the framing information of the subject. The framing information acquiring unit may include a depth sensor or an image sensor, and the framing information may be depth information or image information.

S83: Receive the framing information of the subject acquired by the framing information acquiring unit, analyze the framing information of the subject by using a neural network model, and obtain an analysis result of the satisfaction.

In some embodiments, the satisfaction degree is an analysis result directly output by the neural network model by taking all the pixels of the framing information of the subject as input and processing according to the current training result of the neural network model.

S85: When it is determined that the satisfaction exceeds the satisfaction preset threshold, determining that the shooting condition is currently satisfied, controlling to perform a shooting operation, and at least performing imaging processing by the first image processor of the electronic device to obtain a corresponding photo or video. Wherein, the satisfaction threshold may be 80%, 90%, and the like.

The steps S81 to S85 correspond to the steps S51 to S55 in FIG. 5, respectively, and have the same or upper and lower positions. The specific description can be referred to each other.

Please refer to FIG. 9 , which is a flowchart of a shooting control method in a fifth embodiment of the present application. In the fifth embodiment, the preset model is specifically an image processing algorithm model, and the shooting control method includes the following steps:

S91: When the framing is performed, the framing information acquisition unit acquires the framing information of the subject. The framing information acquiring unit may include a depth sensor or an image sensor, and the framing information may be depth information or image information.

S93: Receive the framing information of the object acquired by the finder information acquiring unit, compare the framing information of the object with the reference image by using an image processing algorithm model, and analyze the similarity between the framing information of the object and the reference image. The result of this analysis.

S95: When it is determined that the similarity exceeds the similarity preset threshold, determining that the shooting condition is currently satisfied, controlling to perform a shooting operation to perform imaging processing at least by the first image processor of the electronic device to obtain a corresponding photo or video.

Optionally, in an implementation manner, the image processing algorithm model includes an expression feature model, and when the captured object includes a human face, the image processing algorithm model compares the framing information of the captured object with the reference image. The analysis result of analyzing the similarity between the framing information of the subject and the reference picture comprises: analyzing the facial expression information in the framing information of the subject by using a face recognition technology to generate a corresponding expression feature vector; The similarity between the framing information and the reference picture is calculated according to the expression feature model and the expression feature vector corresponding to the framing information of the subject.

Further, when the plurality of reference pictures are included, when determining that the similarity exceeds the similarity preset threshold, determining that the shooting condition is currently satisfied comprises: determining that the similarity with any of the reference pictures exceeds the similarity preset threshold When it is determined that the similarity determined by the expression feature vector corresponding to the framing information and the expression feature vector of any of the reference pictures exceeds the similarity preset threshold, it is determined that the shooting condition is currently satisfied.

Optionally, in another implementation manner, the image processing algorithm model includes a gesture feature model, and when the object to be photographed includes a human hand, the image processing algorithm model uses the framing information and the reference of the object to be photographed. The image is compared, and the analysis result of the similarity between the framing information of the object and the reference image is analyzed, including: analyzing the gesture information in the framing information of the object by using image recognition technology, and generating a corresponding gesture feature vector; The similarity between the framing information of the subject and the reference picture is calculated according to the gesture feature model and the gesture feature vector corresponding to the framing information of the subject.

Further, when the plurality of reference pictures are included, when determining that the similarity exceeds the similarity preset threshold, determining that the shooting condition is currently satisfied comprises: determining that the similarity with any of the reference pictures exceeds the similarity preset threshold When it is determined that the similarity between the gesture feature vector corresponding to the framing information and the gesture feature vector of any of the reference pictures exceeds the similarity preset threshold, it is determined that the shooting condition is currently satisfied.

Further, when the plurality of reference pictures are included, when determining that the similarity exceeds the similarity preset threshold, determining that the shooting condition is currently satisfied comprises: determining that the similarity between the framing information and any of the reference pictures exceeds the similarity When the threshold is set, that is, when the similarity determined by the scene feature vector corresponding to the framing information and the scene feature vector of any of the reference pictures exceeds the similarity preset threshold, it is determined that the shooting condition is currently satisfied.

The steps S91 to S95 correspond to the steps S51 to S55 in FIG. 5, respectively, and have the same or upper and lower positions. The specific description can be referred to each other.

Please refer to FIG. 10 , which is a flowchart of a shooting control method in a sixth embodiment of the present application. In the sixth embodiment, the photographing control method includes the following steps:

S101: Acquire framing information of the subject by the framing information acquiring unit when the framing is performed.

S103: Receive the framing information of the subject acquired by the framing information acquiring unit, and analyze the framing information of the subject by using a preset model to obtain an analysis result.

Optionally, the preset model includes an image processing algorithm model, and the step S103 includes: comparing the framing information of the object with the reference image by using an image processing algorithm model to obtain a similarity between the framing information of the object and the reference image. degree.

For example, the image processing algorithm model includes an expression feature model. Optionally, the image processing algorithm model compares the framing information of the object with the reference image to obtain a similarity between the framing information of the object and the reference image. The method includes: analyzing facial expressions in the framing information of the object by using a face recognition technology to generate a corresponding expression feature vector; and calculating the image according to the expression feature model corresponding to the expression feature model and the finder information of the photographic subject The similarity between the framing information of the object and the reference image.

Obviously, as mentioned above, in other embodiments, the analysis result of satisfaction can also be obtained by a neural network model.

S105: When it is determined according to the analysis result that the shooting condition is satisfied, controlling to perform a continuous shooting operation to perform imaging processing by at least the first image processor of the electronic device to obtain a plurality of photos of the current subject.

In some embodiments, the step S105 includes: when the similarity between the framing information of the subject and the reference picture exceeds the similarity preset threshold, determining that the shooting condition is satisfied, and controlling to perform the continuous shooting operation.

In other embodiments, when the analysis result of the satisfaction is obtained by the neural network model, the step S105 may further include: when the satisfaction exceeds the satisfaction preset threshold, determining that the shooting condition is satisfied, and controlling to perform the continuous shooting operation. .

The requirement of the shooting condition when performing the continuous shooting operation may be slightly lower than the requirement when the photographing operation is performed. Specifically, the comparison similarity preset threshold or the satisfaction preset threshold may be slightly lower than the execution of the photographing when performing the continuous shooting operation. The similarity preset threshold or satisfaction preset threshold of the operation comparison.

For example, the similarity preset threshold or the satisfaction preset threshold when performing the continuous shooting operation may be 70%, which is lower than the similarity preset threshold or the satisfaction preset threshold of 80% or higher in performing the photographing operation comparison. .

Thus, continuous shooting is achieved when the best shooting effect is about to be achieved, and a photograph of the best shooting effect in continuous shooting can be ensured. For example, the reference picture is a picture with a laughing expression, and the contrast expression vector is an expression feature vector X2 indicating the degree of the mouth angle rising, and the continuous shooting operation is controlled when it is determined that the mouth angle rises to 70% of the reference picture. The user continues to smile for a short period of time, and the user's smile reaches the maximum level. This expression will be captured by the continuous shooting operation, and the photo that ensures the best shooting effect can be ensured by the continuous shooting operation.

The steps S101 to S105 correspond to the steps S51 to S55 in FIG. 5 respectively, and the descriptions of the same or upper and lower positions are mutually related, and the related descriptions can be referred to each other. The steps S101 to S105 also correspond to steps S81 to S85 in FIG. 8 and respectively correspond to steps S91 to S95 in FIG. 9, and the related descriptions can be referred to each other.

Optionally, as shown in FIG. 10, the shooting control method may further include the following steps:

S107: Analyze a plurality of photos obtained by the continuous shooting operation to determine an optimal photo.

Optionally, in an implementation manner, the step S107 may include: analyzing the multiple photos by using a neural network model to obtain satisfaction, and determining a photo with the highest satisfaction as the best photo.

Optionally, in another implementation manner, the step S107 may include: comparing a plurality of photos obtained by the continuous shooting with the reference image, and determining a photo with the highest similarity with the reference image as the optimal photo.

Optionally, as shown in FIG. 10, the shooting control method may further include:

S109: retain the best photo, and delete other photos obtained by the continuous shooting operation.

In some embodiments, the electronic device includes a memory, a plurality of albums are created in the memory, and the retaining the optimal photo is to store the best photo in a certain album, such as a camera. In the album. Among them, by deleting other photos, it can effectively avoid occupying too much storage space.

Please refer to FIG. 11 , which is a flowchart of a shooting control method in a seventh embodiment of the present application. In the seventh embodiment, the photographing control method includes the following steps:

S111: When the framing is performed, the framing information acquisition unit acquires the framing information of the subject.

S113: Receive the framing information of the subject acquired by the framing information acquiring unit, and analyze the framing information of the subject by using a preset model to obtain an analysis result.

S115: When it is determined that the shooting condition is satisfied according to the analysis result, controlling to perform a video capturing operation to obtain an image of the current subject by at least an imaging process performed by the first image processor of the electronic device.

The requirement of the shooting condition when performing the video shooting operation may also be slightly lower than the requirement when the photographing operation is performed. Specifically, the comparison similarity preset threshold or the satisfaction preset threshold may be slightly lower than the execution when performing the continuous shooting operation. The similarity preset threshold or the satisfaction preset threshold of the photographing operation comparison.

Thus, video shooting is performed when the best shooting effect is about to be achieved, and the video frame frame including the best shooting effect in the video can be ensured.

The steps S111 to S115 respectively correspond to the steps S101 to S105 in the sixth embodiment shown in FIG. 10 . For a more specific introduction, reference may be made to the related description of FIG. 10 . The steps S111-S11 also correspond to the steps S51-S55 in FIG. 5 respectively, and the description relationship of the same or the upper and lower positions is mutually related, and the related descriptions can refer to each other. The steps S111 to S115 also correspond to steps S81 to S85 in FIG. 8 and respectively correspond to steps S91 to S95 in FIG. 9, and the related descriptions can be referred to each other.

Optionally, as shown in FIG. 11, the shooting control method may further include:

S117: Compare a plurality of video picture frames in the captured video to determine an optimal picture frame.

Optionally, in an implementation manner, the step S117 may include: analyzing the plurality of video picture frames by using a neural network model to obtain satisfaction, and determining a video frame with the highest satisfaction as the optimal one. Picture frame.

Optionally, in another implementation manner, the step S117 may include: comparing a plurality of video picture frames in the video with a reference picture, and determining a video picture frame with the highest similarity with the reference picture as the The best picture frame.

S119: The optimal picture frame is cut out and saved as a photo.

In some embodiments, as previously described, the electronic device includes a memory, a plurality of albums are created in the memory, and the "snap the best picture frame is saved as a photo" for the best The frame of the picture is stored in an album in the form of a picture/photo, for example, stored in a camera album.

Please refer to FIG. 12 , which is a flowchart of a shooting control method in an eighth embodiment of the present application. The eighth embodiment is compared with the photographing control method in the first embodiment shown in FIG. 5, in that after controlling the execution of the photographing operation, there is a subsequent step of receiving user satisfaction feedback information, and the photographing control method includes The following steps:

S121: When the framing is performed, the framing information acquisition unit acquires the framing information of the subject.

S123: Receive the framing information of the subject acquired by the framing information acquiring unit, and analyze the framing information of the subject by using a preset model to obtain an analysis result.

S125: When it is determined that the shooting condition is satisfied according to the analysis result, controlling to perform a photographing operation to obtain an image or a video of the current subject at least by performing imaging processing by the first image processor of the electronic device.

S127: Acquire the user's satisfaction feedback information about the automatic shooting.

Optionally, in an implementation manner, after the automatic photographing is completed, the user may be prompted to perform satisfaction evaluation on the automatic photographing by generating prompt information, for example, generating a prompt box including “satisfactory” and “unsatisfactory” options. For the user to select, and according to the user's choice, the satisfaction feedback information of the automatic photographing is obtained.

Optionally, in another embodiment, the user's satisfaction with the automatic shooting is obtained by detecting the user's operation on the photo or video obtained by the automatic shooting. For example, if it is detected that the user deletes the photo or video obtained by the automatic shooting, it is determined that the user is not satisfied with the automatic shooting, and the satisfaction feedback information that is unsatisfactory is obtained. For example, if it is detected that the user has set a photo or video obtained by the automatic shooting to a favorite or favorite type setting operation or a sharing operation, it is determined that the user is satisfied with the automatic shooting, and obtains I got feedback on satisfaction with satisfaction.

S129: Output the satisfaction feedback information of the user to the automatic shooting to the currently used model, so that the currently used model uses the satisfaction feedback information to perform optimization training.

Therefore, in the present application, by collecting user satisfaction feedback information for automatic shooting, the training of the model can be optimized, and the model is continuously optimized, so that the automatic shooting in subsequent use can be more accurate.

The model currently used may be a model that has been confirmed by training, or a model that has not been trained. When it is confirmed that the training is completed, the model can be further optimized. When the model is not yet trained, the training can be better achieved.

The steps S121 to S125 respectively correspond to the steps S101 to S105 in the sixth embodiment shown in FIG. 10 . For a more specific introduction, reference may be made to the related description of FIG. 10 . The steps S121 to S125 also correspond to the steps S51 to S55 in FIG. 5 respectively, and the description relationship of the same or the upper and lower positions is mutually related, and the related descriptions can refer to each other. The steps S121 to S125 also correspond to steps S81 to S85 in FIG. 8 and respectively correspond to steps S91 to S95 in FIG. 9, and the related descriptions can be referred to each other.

Please refer to FIG. 13 , which is a flowchart of a shooting control method in a ninth embodiment of the present application. In the ninth embodiment, the preset model is an untrained model, and is gradually completed with the manual operation performed by the user. The shooting control method includes the following steps:

S131: When the user performs manual control shooting, the currently taken picture is taken as a positive sample satisfying the shooting condition by the model, and the parameters of the model itself are adjusted according to the current positive sample.

In some embodiments, the model saves the frontal sample and establishes or updates the positive sample and the correspondence that satisfies the shooting conditions to adjust the parameters of the model itself. Among them, the photographing condition can be marked as a label of the front sample.

Optionally, in one implementation, the user manually controls the shooting to be done by pressing a shutter button or a photo icon.

Optionally, in another implementation, the user manually controls the shooting to be performed by performing a specific operation on a physical button of the electronic device. For example, the electronic device includes a power button, and manual control shooting is achieved by double-clicking the power button.

S133: Sample a frame obtained by framing between two adjacent manual control shots at a preset time interval as a reverse sample, and adjust parameters of the model according to the reverse sample.

In some embodiments, the model may save the back samples of the samples, and may also establish a correspondence between the back samples and the photographing conditions to adjust the parameters of the model itself. The back surface sample is a screen that does not satisfy the shooting condition; the labeling condition may be used as a label of the back surface sample for marking. The preset time interval may be 1 second, 2 seconds, and the like.

Optionally, in an implementation manner, the two adjacent manual control shots may be two adjacent manual control shots during the framing shooting performed by the same camera opening.

Optionally, in another implementation manner, the two adjacent manual control shots may also be two different manual control shots during the framing shooting process when different cameras are turned on. For example, after the user turns on the camera and completes the first manual control shooting, the camera is turned off, and the next time the camera is turned on to complete the second manual control shooting, the framing screen between the first manual control shooting and the second manual control shooting is The currently used model is saved at a preset time interval as a negative sample.

S135: When it is determined that the training completion condition is reached, the training is ended to obtain the trained model for subsequent automatic shooting control.

Optionally, in an implementation manner, the step S131 further includes the step of: entering the model training mode in response to the user input entering the model training. The determining that the training completion condition is reached includes determining that the training completion condition is reached in response to the user inputting the operation of exiting the model training mode.

Optionally, the operation of entering the model training includes a selection operation of a menu option, or a specific operation on a physical button, or a specific touch gesture input on a touch screen of the electronic device. Optionally, the operation of entering the model training in response to the user input controls the entering the model training mode, including: responding to the user's selection operation of the menu option, or performing a specific operation on the physical button, or inputting on the touch screen of the electronic device. The specific touch gesture is controlled to enter the model training mode.

Optionally, in another implementation manner, the determining that the training completion condition is reached includes: determining that the training completion condition is reached when it is determined that the number of times the user manually controls the shooting reaches the preset number of times N1. The preset number of times N1 may be the number of times the system default model training needs to be performed, or may be a user-defined value.

Optionally, in another implementation manner, the determining that the training completion condition is met includes: using the positive sample of the current time to test the model, determining whether the test result reaches a preset threshold, and determining that the test result reaches a preset threshold, determining The training completion conditions are reached.

Alternatively, in some embodiments, the method steps shown in Figure 13 are performed after the automatic shooting function is turned on. For example, it is performed in response to the user turning on the automatic shooting function in the setting operation in the camera's menu option.

In other embodiments, it may also be determined by some intelligent algorithms whether to perform model training, for example, determining whether to enter the model training mode by determining factors such as the geographic location of the electronic device, the current time, and the like. Specifically, if the electronic device is currently in a geographically frequent location, such as a home, then at this time, the user may not want to take a photo or video of a new location, and entering the model training mode at this time will not be too large. Causes interference with the user's photo.

The above model may be a model such as a neural network model or an image processing algorithm model.

In the present application, the user's training model is customized by the user's shooting operation without using another person's model, so that personalization can be better achieved.

In some embodiments, the models described herein may be programs such as specific algorithm functions running in processor 30, such as neural network algorithm functions, image processing algorithm functions, and the like. In other embodiments, the electronic device 100 may further include a model processor that is independent of the processor 30. The model described in the present application is in an operation and model processor, and the processor 30 may be The model processor is triggered to run the corresponding model according to the need to generate a corresponding instruction, and the output result of the model is output to the processor 30 by the model processor for use by the processor 30, and control such as a shooting operation is performed.

The photographing control method and the electronic device 100 of the present application can automatically determine whether the photographing condition is satisfied according to the photographing information of the photographed object, and perform photographing when the photographing condition is satisfied, and can capture the wonderful content corresponding to the viewfinder information of the currently photographed object in time. moment.

Those skilled in the art will appreciate that embodiments of the present invention can be provided as a method, apparatus (device), or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code. The computer program is stored/distributed in a suitable medium, provided with other hardware or as part of the hardware, or in other distributed forms, such as over the Internet or other wired or wireless telecommunication systems.

The present invention has been described with reference to flowchart illustrations and/or block diagrams of the methods, apparatus, and computer program products of the embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

The above disclosure is only an embodiment of the present application, and of course, the scope of the application should not be limited thereto, and those skilled in the art can understand all or part of the process of implementing the above embodiments, and according to the claims of the present application. The equivalent change is still within the scope of the application.

Claims

A shooting control method, characterized in that the shooting control method comprises:

When the framing is taken, the framing information acquisition unit acquires framing information of the subject;

Receiving the framing information of the subject acquired by the framing information acquiring unit, analyzing the framing information of the subject to obtain an analysis result;

When it is determined according to the analysis result that the photographing condition is satisfied, the photographing operation is controlled to perform at least the image processing by the first image processor to obtain a corresponding photograph or video.
The photographing control method according to claim 1, wherein analyzing the framing information of the subject to obtain an analysis result comprises: analyzing a framing information of the subject by using a preset model to obtain an analysis result .
The photographing control method according to claim 2, wherein the framing information acquiring unit includes a depth sensor, and the framing information acquiring unit acquires framing information of the photographic subject, including: capturing by the depth sensor The depth information of the object;

The analyzing the framing information of the object by using the preset model to obtain the analysis result includes: receiving depth information of the object to be photographed, and analyzing the depth information by using a preset model to obtain the analysis result. .
The photographing control method according to claim 3, wherein the depth sensor comprises at least one of a binocular ranging depth sensor, a structured light depth sensor, and a time-of-flight depth sensor.
The photographing control method according to claim 2, wherein the framing information acquiring unit includes a second image sensor, and the framing information acquiring unit acquires framing information of the photographed object, including: passing the second image The sensor acquires image information of the subject;

The analyzing the framing information of the subject by using the preset model to obtain the analysis result includes: receiving the image information, and analyzing the image information by using a preset model to obtain the analysis result.
The photographing control method according to claim 5, wherein, when it is determined that the photographing condition is satisfied according to the analysis result, controlling to perform a photographing operation to obtain an image or video by at least processing by the first image processor ,include:

When it is determined that the photographing condition control is satisfied according to the analysis result, the photographing operation is simultaneously performed by the first image processor and the second image sensor to obtain a corresponding photograph or video.
The photographing control method according to claim 2, wherein the preset model is a neural network model; and the framing information of the photographed object is analyzed by using a preset model to obtain an analysis result, including:

The framing information of the subject is analyzed by a neural network model, and the analysis result of satisfaction is obtained;

The determining, according to the analysis result, that the shooting condition is met, includes:

When it is determined that the satisfaction exceeds the satisfaction preset threshold, it is determined that the shooting condition is currently satisfied.
The photographing control method according to claim 2, wherein the preset model is an image processing algorithm model, and the framing information of the photographed object is analyzed by using a preset model to obtain an analysis result, including:

The image processing algorithm model is used to compare the framing information of the object with the reference image, and analyze the analysis result of the similarity between the framing information of the object and the reference image;

Determining, according to the analysis result, that the current shooting condition is met, including:

When it is determined that the similarity exceeds the similarity preset threshold, it is determined that the shooting condition is currently satisfied.
The photographing control method according to claim 8, wherein the image processing algorithm model includes an emoticon feature model, and the image processing algorithm model compares the framing information of the photographed object with the reference image, and analyzes the photographed image. The analysis results of the similarity between the framing information of the object and the reference image, including:

Using facial recognition technology to analyze facial expression information in the framing information of the object to generate a corresponding expression feature vector;

The similarity between the framing information of the subject and the reference picture is calculated according to the expression feature vector and the expression feature vector corresponding to the framing information of the subject.
The photographing control method according to claim 8, wherein the image processing algorithm model comprises a gesture feature model, and the image processing algorithm model compares the framing information of the object with the reference image, and analyzes the captured image. The analysis results of the similarity between the framing information of the object and the reference image, including:

The image recognition technology is used to analyze the gesture information in the framing information of the object to generate a corresponding gesture feature vector;

The similarity between the framing information of the subject and the reference picture is calculated according to the gesture feature model and the gesture feature vector corresponding to the framing information of the subject.
The photographing control method according to claim 8, wherein the image processing algorithm model comprises a scene feature model, and the image processing algorithm model compares the framing information of the object with the reference image, and analyzes the photographed image. The analysis results of the similarity between the framing information of the object and the reference image, including:

The image recognition technology is used to analyze the scene information in the framing information of the object to generate a corresponding scene feature vector;

The similarity between the framing information of the subject and the reference picture is calculated according to the scene feature model and the scene feature vector corresponding to the framing information of the subject.
An electronic device, the electronic device comprising:

a framing information acquiring unit, configured to acquire framing information of the subject when shooting the framing;

a first image processor for performing an imaging process;

a memory in which program instructions are stored;

A processor for invoking the program instructions to perform the photographing control method according to any one of claims 1-11.
The electronic device according to claim 12, wherein the framing information acquisition unit includes a depth sensor for acquiring depth information of the subject as the framing information when the framing is taken.
The electronic device of claim 13, wherein the depth sensor comprises at least one of a binocular ranging depth sensor, a structured light depth sensor, and a time of flight depth sensor.
The electronic device according to claim 12, wherein the framing information acquisition unit comprises a second image sensor, and the second image sensor is configured to acquire image information of the photographic subject as the framing when capturing the framing information.
The electronic device of claim 15 wherein the imaging resolution of the second image sensor is lower than the imaging resolution of the first image sensor.
The electronic device according to claim 15, wherein the electronic device comprises a first lens and a second lens, the first lens is disposed corresponding to the image sensor, and the first image sensor is used to pass through The first lens receives the light for performing an imaging process, and the second lens is disposed corresponding to the second image sensor, and the image sensor is configured to acquire the image information of the object by receiving the light through the second lens.
The electronic device according to claim 15, wherein said electronic device comprises a first lens, said first image sensor being disposed side by side with said second image sensor, and each being disposed opposite said first lens.
The electronic device according to claim 18, wherein the area of the second image sensor facing the first lens is smaller than the area of the first image sensor facing the first lens.
A computer readable storage medium, wherein the computer readable storage medium stores program instructions for performing a shooting control according to any one of claims 1 to 11 after being invoked by a computer method.