CN114448952B

CN114448952B - Streaming media data transmission method and device, storage medium and electronic equipment

Info

Publication number: CN114448952B
Application number: CN202011120026.1A
Authority: CN
Inventors: 王少鸣
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2020-10-19
Filing date: 2020-10-19
Publication date: 2023-07-14
Anticipated expiration: 2040-10-19
Also published as: CN114448952A

Abstract

The invention discloses a streaming media data transmission method and device, a storage medium and electronic equipment. Wherein the method comprises the following steps: acquiring streaming media data acquired by image acquisition equipment; under the condition that candidate images containing face image areas are detected from streaming media data, cutting the candidate images according to target sizes corresponding to acquisition resolutions of image acquisition equipment to obtain target images, wherein the target images comprise the face image areas; and transmitting the target streaming media data formed by the cut target image to a background server. The invention solves the technical problem of lower transmission efficiency of streaming media data in the related technology.

Description

Streaming media data transmission method and device, storage medium and electronic equipment

Technical Field

The present invention relates to the field of video transmission technologies, and in particular, to a method and apparatus for transmitting streaming media data, a storage medium, and an electronic device.

Background

At present, the video data collected by cameras installed in each terminal are processed in the following general ways: and uploading the video data to a back-end server in the form of complete streaming media data through an application client running in the terminal, so that the back-end server carries out subsequent processing on the video data.

That is, in the application client provided in the related art, all the collected data is often directly transmitted to the backend server in the form of complete streaming media data through the uplink network. However, the above-mentioned complete streaming media data often further includes a lot of useless information, and these information also occupy a large transmission bandwidth in the transmission process, so that the transmission flow is consumed too much, which results in a technical problem of low transmission efficiency of the streaming media data.

In view of the above problems, no effective solution has been proposed at present.

Disclosure of Invention

The embodiment of the invention provides a streaming media data transmission method and device, a storage medium and electronic equipment, which are used for at least solving the technical problem of low streaming media data transmission efficiency in the related technology.

According to an aspect of an embodiment of the present invention, there is provided a method for transmitting streaming media data, including: acquiring streaming media data acquired by image acquisition equipment; under the condition that a candidate image containing a face image area is detected from the streaming media data, cutting the candidate image according to a target size corresponding to the acquisition resolution of the image acquisition equipment to obtain a target image, wherein the target image comprises the face image area; and transmitting the target streaming media data formed by the cut target images to a background server.

According to another aspect of the embodiment of the present invention, there is also provided a method for transmitting streaming media data, including: acquiring a target image in target streaming media data sent by an application client, wherein the target image is an image obtained by cutting a candidate image by the application client according to a target size corresponding to the acquisition resolution of image acquisition equipment, the candidate image is an image containing a face image area detected in the streaming media data acquired by the image acquisition equipment, and the application client has an association relationship with the image acquisition equipment; acquiring respective corresponding evaluation coefficients of the target images, wherein the evaluation coefficients are used for evaluating the display definition of the face image area; determining a key image according to the evaluation coefficient; and sending the key image to the application client.

According to still another aspect of the embodiment of the present invention, there is also provided a transmission apparatus for streaming media data, including: the first acquisition unit is used for acquiring the streaming media data acquired by the image acquisition equipment; a clipping unit, configured to clip, when a candidate image including a face image area is detected from the streaming media data, the candidate image according to a target size corresponding to a collection resolution of the image collection device, so as to obtain a target image, where the target image includes the face image area; and the transmission unit is used for transmitting the target streaming media data formed by the cut target images to a background server.

Optionally, the clipping unit includes: a first determining subunit, configured to determine hardware attribute information of the image capturing device; the second acquisition subunit is used for acquiring the target size corresponding to the acquisition resolution of the image acquisition equipment according to the hardware attribute information; and the first clipping subunit is used for clipping the candidate image according to the target size to obtain the target image.

Optionally, the second obtaining subunit includes: the third acquisition module is used for acquiring model information of the image acquisition equipment in the hardware attribute information, wherein the model information corresponds to the acquisition resolution of the image acquisition equipment one by one; and a fourth acquisition module for acquiring the target size matched with the model information.

Optionally, the fourth obtaining module includes: the first sending submodule is used for sending a configuration request carrying the model information to the background server; the first obtaining sub-module is used for obtaining the image configuration parameters matched with the model information and returned by the background server in response to the configuration request, wherein the image configuration parameters are used for indicating the target size matched with the model information.

Optionally, the first clipping subunit further comprises: a first determining module, configured to determine a position coordinate of a region center of the face image region in the candidate image; and the first clipping module is used for clipping the candidate image according to the target size by taking the position coordinates as the circle center so as to obtain the target image comprising the face image area.

Optionally, the apparatus further includes: a first detection unit, configured to perform face detection on an image in the streaming media data through a face image detection model configured in an application client associated with the image acquisition device; and the first determining unit is used for determining the current image as the candidate image when the current image is detected to contain the face image area.

Optionally, the apparatus further includes: a first receiving unit configured to receive identity information of a target object identified by the background server from the face image area of the target image; and the first verification unit is used for determining the target object as a legal object under the condition that the identity information of the target object reaches the verification condition.

According to still another aspect of the embodiment of the present invention, there is also provided a transmission apparatus for streaming media data, including: a first obtaining unit, configured to obtain a target image in target streaming media data sent by an application client, where the target image is an image obtained by clipping a candidate image by the application client according to a target size corresponding to an acquisition resolution of an image acquisition device, and the candidate image is an image including a face image area detected in streaming media data acquired by the image acquisition device, and the application client has an association relationship with the image acquisition device; a second obtaining unit, configured to obtain an evaluation coefficient corresponding to each of the target images, where the evaluation coefficient is used to evaluate display sharpness of the face image area; the determining unit is used for determining a key image according to the evaluation coefficient; and the sending unit is used for sending the key image to the application client.

Optionally, the apparatus further includes: the identification unit is used for inputting the key images into a face identification model to obtain an identification result, wherein the face identification model is a neural network model for identifying face images after training by utilizing a plurality of sample images; and the second determining unit is used for determining the identity information of the target object displayed in the face image area of the key image according to the identification result.

Optionally, the apparatus further includes: the first receiving unit is used for receiving a configuration request sent by the application client, wherein the configuration request carries model information of the image acquisition equipment, and the model information corresponds to the acquisition resolution of the image acquisition equipment one by one; a first response unit, configured to obtain a target image configuration parameter configured for the model information in response to the configuration request, where the target image configuration parameter is used to indicate the target size matched with the model information; and the first sending unit is used for sending the target image configuration parameters to the application client so that the application client cuts according to the target size to obtain the target image.

Optionally, the apparatus further includes: the first configuration unit is used for setting image configuration parameters for image acquisition equipment of different types, wherein the types of the image acquisition equipment are in one-to-one correspondence with the acquisition resolutions of the image acquisition equipment, and the image configuration parameters are used for indicating the cutting sizes matched with the types; and the first storage unit is used for storing the image configuration parameters into a background database.

According to still another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above-described streaming media data transmission method when executed.

According to still another aspect of the embodiments of the present invention, there is further provided an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the streaming media data transmission method described above through the computer program.

In the embodiment of the invention, streaming media data acquired by image acquisition equipment is adopted; under the condition that a candidate image containing a face image area is detected from the streaming media data, cutting the candidate image according to a target size corresponding to the acquisition resolution of the image acquisition equipment to obtain a target image, wherein the target image comprises the face image area; and transmitting the target streaming media data formed by the cut target images to a background server. According to the method, the candidate image is cut according to the target size corresponding to the acquisition resolution of the image acquisition equipment to obtain the target image, and then the target streaming media data containing the target image is transmitted to the background server, so that the aim of reducing the occupied bandwidth of streaming media data transmission is fulfilled, the technical effects of reducing the streaming media data transmission flow consumption and improving the streaming media data transmission efficiency are realized, and the technical problem of lower streaming media data transmission efficiency in the related art is solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:

fig. 1 is a schematic diagram of an application environment of an alternative streaming media data transmission method according to an embodiment of the present invention;

fig. 2 is a schematic diagram of an application environment of another alternative streaming media data transmission method according to an embodiment of the present invention;

fig. 3 is a schematic diagram of an application environment of yet another alternative streaming media data transmission method according to an embodiment of the present invention;

fig. 4 is a flowchart of an alternative streaming media data transmission method according to an embodiment of the present invention;

fig. 5 is a schematic diagram of an image cropping process of an alternative streaming media data transmission method according to an embodiment of the present invention;

fig. 6 is a flowchart of an alternative streaming media data transmission method according to an embodiment of the present invention;

fig. 7 is an interactive flow diagram of an alternative streaming media data transmission method according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of an alternative streaming media data transmission method according to an embodiment of the present invention;

Fig. 9 is a schematic structural diagram of an alternative streaming media data transmission device according to an embodiment of the present invention;

fig. 10 is a schematic structural diagram of another alternative streaming media data transmission device according to an embodiment of the present invention;

FIG. 11 is a schematic diagram of an alternative electronic device according to an embodiment of the invention;

fig. 12 is a schematic structural view of another alternative electronic device according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

According to an aspect of the embodiment of the present invention, there is provided a method for transmitting streaming media data, optionally, as an optional implementation manner, the method for transmitting streaming media data may be, but is not limited to, applied to an application environment as shown in fig. 1. The application environment comprises the following steps: a terminal device 102, a network 104 and a server 106 which interact with a user in a man-machine manner. Man-machine interaction can be performed between the user 108 and the terminal device 102, and a transmission application client of streaming media data runs in the terminal device 102. The terminal device 102 includes an image capture device 1022, a processor 1024 and a memory 1026. The image capturing device 1022 is configured to obtain streaming media data; the processor 1024 is configured to obtain, when a candidate image including a face image area is detected from the streaming media data, a target image by clipping the candidate image according to a target size corresponding to a capture resolution of the image capture device, where the target image includes the face image area. The memory 1026 is used for storing the streaming media data and for the target image.

In addition, the server 106 includes a database 1062 and a processing engine 1064, where the database 1062 is used for storing and acquiring a target image in the target streaming media data sent by the application client, and storing a target size corresponding to the acquisition resolution of the image acquisition device 1022. The processing engine 1064 is configured to query the target data resource according to the data resource management request, and perform a management operation on the target data resource to obtain an operation result.

The specific process comprises the following steps: assuming that a streaming media data transmission application client is running in the terminal device 102 as shown in fig. 1, the user 108 operates the image capturing device 1022 to manage and operate the streaming media data, as shown in steps S102-S104, and in the case that the streaming media data captured by the image capturing device detects a candidate image including a face image area from the streaming media data, the candidate image is clipped according to a target size corresponding to the capturing resolution of the image capturing device, so as to obtain a target image, where the target image includes the face image area. Then, step S110 is executed to send the target streaming media data composed of the clipped target image to the server 106 through the network 104. Step S112-S116, obtaining a target image in target streaming media data sent by an application client, wherein the target image is an image obtained by cutting a candidate image according to a target size corresponding to the acquisition resolution of image acquisition equipment by the application client, and the candidate image is an image containing a face image area detected in the streaming media data acquired by the image acquisition equipment, and the application client has an association relation with the image acquisition equipment; acquiring respective corresponding evaluation coefficients of each target image, wherein the evaluation coefficients are used for evaluating the display definition of the face image area; and determining the key image according to the evaluation coefficient. And notifies the terminal device 102 through the network 104 to return the above-described key image as by step S118.

As another alternative embodiment, the data resource management method described above may be applied to the application environment shown in fig. 2. As shown in fig. 2, a user 202 may interact with a terminal device 204. The terminal device 204 includes a memory 206 and a processor 208. The terminal device 204 in this embodiment may, but is not limited to, refer to performing the operations performed by the terminal device 102 described above to obtain the key image obtained by the management operation on the target streaming media data.

As yet another alternative embodiment, the method for transmitting streaming media data described above in the present application may be applied to fig. 3. As shown in fig. 3, a user 302 may interact with a terminal device 304. The terminal device 304 includes a memory 306 and a processor 308. Terminal device 304 may interact with data via network 310 and server 312. The server 312 includes a database 314 for storing interaction data; and a processing engine 316 for processing the interaction data. The server 312 may interact with the terminal devices 318 via the network 310. The terminal device 318 may interact with the user 320, and the terminal device 318 includes a memory 322 and a processor 324. In addition, the terminal device 304 may display the face image of the user 302 and the user information thereof, the terminal device 318 may display the face image of the user 320 and the user information thereof, and the terminal device 304 or the terminal device 318 may acquire the key image in the streaming media data by referring to the operations performed by the terminal device 102.

Optionally, the terminal device 102, the terminal device 204, the terminal device 304, and the terminal device 318 may be, but not limited to, mobile phones, tablet computers, notebook computers, PCs, and other terminals, and the network 104, 310 may include, but is not limited to, wireless networks or wired networks. Wherein the wireless network comprises: WIFI and other networks that enable wireless communications. The wired network may include, but is not limited to: wide area network, metropolitan area network, local area network. The servers 112, 312 may include, but are not limited to, any hardware device capable of performing calculations.

Optionally, as an optional implementation manner, as shown in fig. 4, the method for transmitting streaming media data includes:

s402, acquiring streaming media data acquired by image acquisition equipment;

s404, under the condition that a candidate image containing a face image area is detected from streaming media data, cutting the candidate image according to a target size corresponding to the acquisition resolution of the image acquisition equipment to obtain a target image, wherein the target image comprises the face image area;

s406, transmitting the target streaming media data formed by the cut target image to a background server.

In step S402, in practical application, the image capturing device may be a camera or a scanner of different types, or a 3D camera, where software and hardware related to biological signals are built in the 3D camera, for example, including a depth camera and/or an infrared camera, so that information security of a user can be well ensured; the depth camera can acquire face pictures with depth information, and the infrared camera can acquire face pictures with infrared information; the image capturing device may also be various electronic image capturing devices including a combination of cameras or scanners, without limitation. Streaming media data refers to data transmitted in a network by sectionally transmitting a series of media data in a streaming mode after compressing the media data; the streaming media data may include data such as a sound stream, a video stream, a text stream, an image stream, and a moving picture stream. Typical streaming data formats may include, but are not limited to MPEG, AVI, DVI and SWF, etc. Further, the image pickup apparatus may be a combination of the above-described plurality of image pickup apparatuses.

In step S404, in the case of detecting a candidate image including a face image area from the streaming media data during actual application, that is, the current image capturing device captures the streaming media data including a plurality of frames of pictures including the face image area, the candidate image is a set of the plurality of frames of pictures including the face image area. Cutting the candidate images according to a target size corresponding to the acquisition resolution of the image acquisition equipment to obtain target images, wherein the target images comprise a face image area; for example, the current image capturing device has a capturing resolution of 480×640 pixels, the target size corresponding to the resolution is 60×60 pixels, and the candidate image is clipped to obtain a target image with 60×60 pixels.

In step S406, during actual application, the target streaming media data formed by the clipped target image is transmitted to the background server, that is, the current streaming media data acquired by the image acquisition device includes multiple frames of pictures including the face image area, and then the clipped target image forms the target streaming media data and is sent to the background service. For example, the current image acquisition device has an acquisition resolution of 480×640 pixels, the resolution corresponds to a target size of 60×60 pixels, and the target image obtained by cutting 60×60 pixels forms target stream data and is transmitted to a background server for subsequent operation.

According to the embodiment of the invention, the candidate image is cut according to the target size corresponding to the acquisition resolution of the image acquisition equipment to obtain the target image, and then the target streaming media data containing the target image is transmitted to the background server, so that the aim of reducing the occupied bandwidth of streaming media data transmission is fulfilled, the technical effects of reducing the streaming media data transmission flow consumption and improving the streaming media data transmission efficiency are realized, and the technical problem of lower streaming media data transmission efficiency in the related technology is solved.

In an embodiment, step S404 may include the following steps: determining hardware attribute information of the image acquisition equipment; acquiring a target size corresponding to the acquisition resolution of the image acquisition equipment according to the hardware attribute information; and cutting the candidate image according to the target size to obtain a target image. The above hardware attribute information may include a model number, resolution, definition, signal-to-noise ratio, white balance, and the like of the device, and in this embodiment, may include, but is not limited to, acquiring, according to the hardware attribute information, a target size corresponding to the acquisition resolution of the image acquisition device, for example, the higher the acquisition resolution of the image acquisition device, the smaller the corresponding target size thereof; the lower the acquisition resolution of the image acquisition equipment is, the larger the corresponding target size is; for example, when the acquisition resolution of the image acquisition device is 1920×1080 pixels, the corresponding target size may be 2 inches, and at this time, the candidate image is cut according to the size of 2 inches to obtain a target image containing the face image with the size of 2 inches; when the acquisition resolution of the image acquisition device is 640 x 480 pixels, the corresponding target size of the image acquisition device may be 4 inches, and at this time, the candidate image is cut according to the size of 4 inches to obtain a target image containing the face image with the size of 4 inches. In this embodiment, by determining the acquisition resolution of the image acquisition device and the corresponding target size thereof, the accuracy of acquiring the target image can be improved, and the transmission efficiency can be improved.

In an embodiment, acquiring a target size corresponding to an acquisition resolution of the image acquisition device according to the hardware attribute information includes: the method comprises the steps of obtaining model information of image acquisition equipment in hardware attribute information, wherein the model information corresponds to acquisition resolution of the image acquisition equipment one by one; and obtaining the target size matched with the model information. For example, in the obtained hardware attribute information, the model of the image capturing device is a100 or a200, the capturing resolution of the a100 device is 1920×1080 pixels, the capturing resolution of the a100 device is 640×480 pixels, and then the application client may obtain, from the background server, that the corresponding target size of the a100 is 2 inches, and that of the a200 is 4 inches.

In one embodiment, obtaining the target size that matches the model information includes: transmitting a configuration request carrying model information to a background server; and acquiring an image configuration parameter matched with the model information returned by the background server in response to the configuration request, wherein the image configuration parameter is used for indicating a target size matched with the model information. For example, the application client acquires the model A100 of the current image acquisition device, then sends a configuration request of the model to the background server, and after responding to the configuration request, the server returns image configuration parameters matched with the image acquisition device A100, wherein the configuration parameters indicate that the size of the target is 2 inches.

In an embodiment, step S404 may include the following steps: determining the position coordinates of the region center of a face image region in the candidate image; and cutting the candidate image according to the target size by taking the position coordinates as the circle center to obtain a target image comprising a face image area. As shown in fig. 5, the resolution of one candidate image 502 (i.e. the acquired bare data in the figure) acquired by the image acquisition device is 640×480 pixels, the application client determines the position coordinates 504 of the area center of the face image area in the current candidate image, and cuts the current candidate image by using the position coordinates 504 as the center of a circle and according to the pixels with the target size 60×60, so as to obtain the target image 506 including the face image area. Wherein the face image area in the candidate image, i.e. the position of the face in the candidate image, is determined, here a directional gradient histogram (Historarm of Oriented Gradient, HOG) can be used to detect the face position. The candidate image is now grayed, then the gradients of the pixels in the image are calculated, and then the candidate image is converted into HOG form, so that the face position can be obtained.

In an embodiment, step S402 may be followed by the following steps: performing face detection on images in streaming media data through a face image detection model configured in an application client associated with the image acquisition device; and under the condition that the current image contains the face image area, determining the current image as a candidate image. In the embodiment of the invention, the face detection models with different magnitudes are obtained according to different calculation forces of equipment. For example, the model file size is on the order of hundreds of KB, and the backend may be on the order of G. The computational unit at the input resolution of 640x480 is 200 mflips in terms of model computation. For example, a 1M ultra lightweight generic face detection model may be employed that filters out faces below 10×10 pixels through a training set of face data under +/data, and then performs face detection based on the training set of face data to determine whether the current image is a candidate. In terms of model size, the size of a default FP32 precision (.pth) file is 1.1MB, and the size of an inference frame int8 after quantization is about 300 KB. In terms of model calculation amount, the input resolution of 320x240 is only about 90-109 mflips, and the model calculation amount is light enough. The model is designed with two versions, version-slide (the main body is simplified at a slightly higher speed), version-RFB (a modified RFB module is added, the precision is higher), the model provides a pre-training model trained by using windows under different input resolutions of 320x240, 640x480 and the like, and the model works better in different application scenes. And no special operator is used, onnx export is supported, and the migration reasoning is convenient. The face detection can be carried out on the image in the streaming media data through the 1M ultra-lightweight general face detection model; and under the condition that the current image contains the face image area, determining the current image as a candidate image.

In an embodiment, step S406 may be followed by the following steps: receiving identity information of a target object identified by a background server from a face image area of the target image; and under the condition that the identity information of the target object reaches the verification condition, determining that the target object is a legal object. For example, after the server identifies the user identity information of the target object from the face image area of the target image, the user identity information is sent to the application client, the application client compares the user identity information with the member information, and if the current user is determined to be a member, the application client automatically jumps to a member module corresponding to the application client. In the embodiment of the invention, the current user is judged to be a member through the identity information of the target object identified by the background server, so that the step that the user manually inputs personal account information is reduced, the operation flow is simplified, and the user experience is improved.

Optionally, as an optional implementation manner, as shown in fig. 6, the method for transmitting streaming media data includes:

s602, acquiring a target image in target streaming media data sent by an application client, wherein the target image is an image obtained by cutting a candidate image according to a target size corresponding to the acquisition resolution of image acquisition equipment by the application client, and the candidate image is an image containing a face image area detected in the streaming media data acquired by the image acquisition equipment, and the application client has an association relation with the image acquisition equipment;

s604, acquiring respective corresponding evaluation coefficients of each target image, wherein the evaluation coefficients are used for evaluating the display definition of the face image area;

s606, determining a key image according to the evaluation coefficient;

and S608, sending the key image to the application client.

In step S602, during actual application, the server receives a target image in a target streaming media from an application client through a wired or wireless network; wherein the wireless network comprises: WIFI and other networks that enable wireless communications. The wired network may include, but is not limited to: wide area network, metropolitan area network, local area network.

In step S604, in actual application, the plurality of target objects correspond to different evaluation coefficients, and in this embodiment, the display definition of the face image area is represented by the evaluation coefficients, for example, a graph with the best definition of the face image area in the plurality of target images is selected as the key image. The evaluation coefficient is based on four facial features of face symmetry, definition, illumination instruction and image resolution, and the weighting fusion of the facial features is carried out by using the weight which is automatically adjusted, so that a score of picture quality is finally generated. Wherein the facial symmetry may use the similarity score between histograms of local features (left and right faces) as a local scale; definition the facial feature detector finds facial feature points to construct a mask, no background pixels exist on the mask, and the definition is determined according to the average laplace operator of the mask. The illumination quality is calculated by determining the length of the usable range of gray intensities. For example, the weight coefficient of face symmetry is set to 0.2, the weight coefficient of definition is set to 0.3, the weight coefficient of illumination quality is set to 0.2, and the weight coefficient of image resolution is set to 0.3, then the score of picture quality=face symmetry 0.2+definition 0.3+illumination quality 0.2+image resolution 0.3. Here, one picture with the highest picture quality score may be selected as the key image. Here, one of the pictures having the highest score in picture quality may be selected as the key image.

In an embodiment, step S606 may be followed by the following steps: inputting the key images into a face recognition model to obtain a recognition result, wherein the face recognition model is a neural network model for recognizing the face images after training by utilizing a plurality of sample images; and determining the identity information of the target object displayed in the face image area of the key image according to the identification result. Here, the step of the face detection model identifying the face image may be: reading an input image to be recognized, detecting the position of a human face and the position information of key points in the image to be recognized, preprocessing the image to be recognized according to the position information of the human face and the position information of the key points, and inputting the preprocessed image to be recognized into a sequencing neural network model to obtain the characteristic expression of the image to be recognized; and calculating the similarity between the feature expression of the image to be identified and the features of the known face image in the database to identify the image to be identified.

In an embodiment, the step S602 may be preceded by the following steps: receiving a configuration request sent by an application client, wherein the configuration request carries model information of the image acquisition equipment, and the model information corresponds to the acquisition resolution of the image acquisition equipment one by one; responding to the configuration request, and acquiring a target image configuration parameter configured for the model information, wherein the target image configuration parameter is used for indicating a target size matched with the model information; and sending the target image configuration parameters to the application client so that the application client cuts according to the target size to obtain the target image. For example, in the hardware attribute information acquired by the server, the model of the image acquisition device is a100 or a200, the acquisition resolution of the a100 device is 1920×1080 pixels, and the acquisition resolution of the a100 device is 640×480 pixels, so that the table server acquires that the corresponding target size of the a100 is 2 inches, the corresponding target size of the a200 is 4 inches, and then sends the corresponding target sizes of the a100 and the a200 to the application client.

In an embodiment, the step S602 may be preceded by the following steps: setting image configuration parameters for different types of image acquisition equipment, wherein the types of the image acquisition equipment are in one-to-one correspondence with the acquisition resolutions of the image acquisition equipment, and the image configuration parameters are used for indicating the cutting sizes matched with the types; and storing the image configuration parameters into a background database. For example, before mass production, the image acquisition device needs to be calibrated for each model of image acquisition device, and the current image acquisition device outputs a cutting size corresponding to the current image acquisition device according to the face recognition effect; image configuration parameters like { type } "A100", width } "60", height } "60", type } "A200", width } "40", height } "40", etc. are formed. The server stores the image configuration parameters in a background database for calling by the application client.

Optionally, as an optional embodiment, as shown in fig. 7, the method for transmitting streaming media data includes:

s702, an application client acquires streaming media data acquired by image acquisition equipment;

s704, under the condition that the application client detects a candidate image containing a face image area from streaming media data, cutting the candidate image according to a target size corresponding to the acquisition resolution of the image acquisition equipment to obtain a target image, wherein the target image comprises the face image area;

s706, the application client transmits the target streaming media data formed by the cut target image to the background server;

S708, the background server acquires a target image in target streaming media data sent by the application client, wherein the target image is an image obtained by cutting a candidate image according to a target size corresponding to the acquisition resolution of the image acquisition device by the application client, and the candidate image is an image containing a face image area detected in the streaming media data acquired by the image acquisition device, and the application client has an association relationship with the image acquisition device;

s710, the background server acquires evaluation coefficients corresponding to each target image, wherein the evaluation coefficients are used for evaluating the display definition of the face image area;

s712, the background server determines a key image according to the evaluation coefficient;

and S714, the background server sends the key image to the application client.

Alternatively, as an optional application embodiment, as shown in fig. 8, the method for transmitting streaming media data includes: step 1, before mass production, the cameras 821 in the terminal device 82 (i.e. the image capturing device in the foregoing embodiment) need to be calibrated for each model camera, and the corresponding streaming media data image is output according to the current camera 821 and cut to size. After the face recognition effect of the data after the size carrier is actually verified, the model and configuration of the camera 824 are stored in a background Database (DB) 844 to form data like { type: "A100", width: "60", height: "60" }, { type: "A200", width: "40", height: "40" }, and the like. Step 2, after the application client 822 (i.e. the face APP) is started, the camera model information is read from the current camera 821, and a configuration request service is initiated to the background server 84 to request the face image configuration service module 822c corresponding to the current camera. Step 3, the camera 821 collects and outputs the original bare data (i.e. the streaming media data collected by the image collecting device in the foregoing embodiment) to the application client 822 (i.e. the face APP in the figure), and the face APP end sends the original bare data to the face detection model 822b to detect the face region, and returns to the center coordinate of the current face after the face region is detected, i.e. the face position is successfully identified. The application client 822 reads the face image configuration, combines the face center coordinates, and cuts the image in the streaming media data through the bare data cutting service module 822a to obtain the face image with the target size. Step 4, after obtaining the face image with the target size, the face APP transmits the face image to the streaming media service module 841 of the background server through the network, and the cut streaming media data image is input into the face recognition service module 842 for face optimization, so as to select the optimal graph, i.e. the graph with the highest quality of the face image. And step 5, finally, the quality optimal diagram in the selected face recognition diagram is sent to a recognition service, after the recognition is successful, the result is returned to the face APP end, and then the face APP end can call other back-end services, such as a member service module 843, based on the result.

It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present invention.

According to another aspect of the embodiment of the present invention, there is also provided a transmission device for implementing the above streaming media data. As shown in fig. 9, the apparatus includes:

A first obtaining unit 902, configured to obtain streaming media data collected by the image collecting device;

a cropping unit 904, configured to crop, when a candidate image including a face image area is detected from the streaming media data, the candidate image according to a target size corresponding to a collection resolution of the image collection device, so as to obtain a target image, where the target image includes the face image area;

and a transmission unit 906, configured to transmit the target streaming media data formed by the clipped target image to the background server.

In the embodiment of the application, the image acquisition equipment can be cameras or scanners of different types or 3D cameras, and software and hardware related to biological signals are arranged in the 3D cameras, such as a depth camera and an infrared camera, so that the information safety of users can be well ensured; the depth camera can acquire face pictures with depth information, and the infrared camera can acquire face pictures with infrared information; the image capturing device may also be various electronic image capturing devices including a combination of cameras or scanners, without limitation. Streaming media data refers to data transmitted in a network by sectionally transmitting a series of media data in a streaming mode after compressing the media data; the streaming media data may include data such as a sound stream, a video stream, a text stream, an image stream, and a moving picture stream. Typical streaming data formats may include, but are not limited to MPEG, AVI, DVI and SWF, etc. Further, the image pickup apparatus may be a combination of the above-described plurality of image pickup apparatuses.

In the embodiment of the present application, when a candidate image including a face image area is detected from the streaming media data, that is, the streaming media data acquired by the current image acquisition device includes multiple frames of pictures including the face image area, the candidate image is a set of multiple frames of pictures including the face image area. Cutting the candidate images according to a target size corresponding to the acquisition resolution of the image acquisition equipment to obtain target images, wherein the target images comprise a face image area; for example, the current image capturing device has a capturing resolution of 480×640 pixels, the target size corresponding to the resolution is 60×60 pixels, and the candidate image is clipped to obtain a target image with 60×60 pixels.

In this embodiment of the present application, the target streaming media data formed by the clipped target image is transmitted to the background server, that is, the current streaming media data acquired by the image acquisition device includes multiple frames of pictures including the face image area, and then the clipped target image forms the target streaming media data and is sent to the background service. For example, the current image acquisition device has an acquisition resolution of 480×640 pixels, the resolution corresponds to a target size of 60×60 pixels, and the target image obtained by cutting 60×60 pixels forms target stream data and is transmitted to a background server for subsequent operation.

Other examples of this embodiment can be found in the above embodiments, and will not be described here.

According to another aspect of the embodiment of the present invention, there is also provided a transmission device for implementing the above streaming media data. As shown in fig. 10, the apparatus includes:

a first obtaining unit 1002, configured to obtain a target image in target streaming media data sent by an application client, where the target image is an image obtained by clipping a candidate image according to a target size corresponding to an acquisition resolution of an image acquisition device by the application client, and the candidate image is an image including a face image area detected in streaming media data acquired by the image acquisition device, and the application client has an association relationship with the image acquisition device;

a second obtaining unit 1004, configured to obtain an evaluation coefficient corresponding to each target image, where the evaluation coefficient is used to evaluate display sharpness of the face image area;

a determining unit 1006, configured to determine a key image according to the evaluation coefficient;

and a sending unit 1008, configured to send the key image to the application client.

In the embodiment of the application, a server receives a target image in a target streaming media through a wired or wireless network by an application client; wherein the wireless network comprises: WIFI and other networks that enable wireless communications. The wired network may include, but is not limited to: wide area network, metropolitan area network, local area network.

In this embodiment of the present application, the plurality of target objects correspond to different evaluation coefficients, and in this embodiment, the display sharpness of the face image area is represented by the evaluation coefficients, for example, one image with the best sharpness of the face image area in the plurality of target images is selected as the key image. The evaluation coefficient is based on four facial features of face symmetry, definition, illumination instruction and image resolution, and the weighting fusion of the facial features is carried out by using the weight which is automatically adjusted, so that a score of picture quality is finally generated. Wherein the facial symmetry may use the similarity score between histograms of local features (left and right faces) as a local scale; definition the facial feature detector finds facial feature points to construct a mask, no background pixels exist on the mask, and the definition is determined according to the average laplace operator of the mask. The illumination quality is calculated by determining the length of the usable range of gray intensities. For example, the weight coefficient of face symmetry is set to 0.2, the weight coefficient of definition is set to 0.3, the weight coefficient of illumination quality is set to 0.2, and the weight coefficient of image resolution is set to 0.3, then the score of picture quality=face symmetry 0.2+definition 0.3+illumination quality 0.2+image resolution 0.3. Here, one picture with the highest picture quality score may be selected as the key image. Here, one of the pictures having the highest score in picture quality may be selected as the key image.

According to a further aspect of the embodiments of the present invention, there is also provided an electronic device for implementing the above-mentioned streaming media data transmission method, as shown in fig. 11, the electronic device comprising a memory 1102 and a processor 1104, the memory 1102 storing a computer program, the processor 1104 being arranged to execute the steps of any of the above-mentioned method embodiments by means of the computer program.

Alternatively, in this embodiment, the electronic apparatus may be located in at least one network device of a plurality of network devices of the computer network.

Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:

acquiring streaming media data acquired by image acquisition equipment;

under the condition that candidate images containing face image areas are detected from streaming media data, cutting the candidate images according to target sizes corresponding to acquisition resolutions of image acquisition equipment to obtain target images, wherein the target images comprise the face image areas;

and transmitting the target streaming media data formed by the cut target image to a background server.

Alternatively, it will be understood by those skilled in the art that the structure shown in fig. 11 is only schematic, and the electronic device may also be a terminal device such as a smart phone (e.g. an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, and a mobile internet device (Mobile Internet Devices, MID), a PAD, etc. Fig. 11 is not limited to the structure of the electronic device. For example, the electronic device may also include more or fewer components (e.g., network interfaces, etc.) than shown in FIG. 11, or have a different configuration than shown in FIG. 11.

The memory 1102 may be used to store software programs and modules, such as program instructions/modules corresponding to the streaming media data transmission method and apparatus in the embodiment of the present invention, and the processor 1104 executes the software programs and modules stored in the memory 1102 to perform various functional applications and data processing, that is, implement the streaming media data transmission method described above. Memory 1102 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 1102 may further include memory located remotely from processor 1104, which may be connected to the terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The memory 1102 may be, but not limited to, for storing information such as a face image in the streaming media data and parameters of the image capturing device. As an example, as shown in fig. 11, the memory 1102 may include, but is not limited to, a first acquiring unit 902, a clipping unit 904, and a transmitting unit 906 in a transmitting device including the streaming media data. In addition, other module units in the streaming media data transmission device may be included, but are not limited to, and are not described in detail in this example.

Optionally, the transmission device 1106 is used to receive or transmit data via a network. Specific examples of the network described above may include wired networks and wireless networks. In one example, the transmission device 1106 includes a network adapter (Network Interface Controller, NIC) that may be connected to other network devices and routers via a network cable to communicate with the internet or a local area network. In one example, the transmission device 1106 is a Radio Frequency (RF) module for communicating wirelessly with the internet.

In addition, the electronic device further includes: a display 1108 for displaying a face detection image; and a connection bus 1110 for connecting the respective module parts in the above-described electronic apparatus.

According to a further aspect of the embodiments of the present invention, there is also provided an electronic device for implementing the above-mentioned streaming media data transmission method, as shown in fig. 12, the electronic device including a memory 1202 and a processor 1204, the memory 1202 storing a computer program, the processor 1204 being configured to execute the steps of any of the above-mentioned method embodiments by means of the computer program.

acquiring a target image in target streaming media data sent by an application client, wherein the target image is an image obtained by cutting a candidate image by the application client according to a target size corresponding to the acquisition resolution of image acquisition equipment, and the candidate image is an image containing a face image area detected in the streaming media data acquired by the image acquisition equipment, and the application client has an association relationship with the image acquisition equipment;

acquiring respective corresponding evaluation coefficients of each target image, wherein the evaluation coefficients are used for evaluating the display definition of the face image area;

determining a key image according to the evaluation coefficient;

and sending the key image to the application client. Alternatively, it will be understood by those skilled in the art that the structure shown in fig. 12 is only schematic, and the electronic device may also be a terminal device such as a smart phone (e.g. an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, and a mobile internet device (Mobile Internet Devices, MID), a PAD, etc. Fig. 12 is not limited to the structure of the electronic device. For example, the electronic device may also include more or fewer components (e.g., network interfaces, etc.) than shown in FIG. 12, or have a different configuration than shown in FIG. 12.

The memory 1202 may be used to store software programs and modules, such as program instructions/modules corresponding to the streaming media data transmission method and apparatus in the embodiments of the present invention, and the processor 1204 executes the software programs and modules stored in the memory 1202 to perform various functional applications and data processing, that is, implement the streaming media data transmission method described above. Memory 1202 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 1202 may further include memory located remotely from the processor 1204, which may be connected to the terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The memory 1202 may be, but not limited to, a memory for storing information such as a face image in streaming media data and parameters of an image acquisition device. As an example, as shown in fig. 12, the memory 1202 may include, but is not limited to, a first acquisition unit 1002, a second acquisition unit 1004, a determination unit 1006, and a transmission unit 1008 in a transmission device of the streaming media data. In addition, other module units in the streaming media data transmission device may be included, but are not limited to, and are not described in detail in this example.

Optionally, the transmission device 1206 is configured to receive or transmit data via a network. Specific examples of the network described above may include wired networks and wireless networks. In one example, the transmission means 1206 comprises a network adapter (Network Interface Controller, NIC) that can be connected to other network devices and routers via a network cable to communicate with the internet or a local area network. In one example, the transmission device 1206 is a Radio Frequency (RF) module for communicating wirelessly with the internet.

In addition, the electronic device further includes: a display 1208 for displaying the face detection image; and a connection bus 1210 for connecting the respective module parts in the above-described electronic device.

In other embodiments, the terminal device or the server may be a node in a distributed system, where the distributed system may be a blockchain system, and the blockchain system may be a distributed system formed by connecting the plurality of nodes through a network communication. Among them, the nodes may form a Peer-To-Peer (P2P) network, and any type of computing device, such as a server, a terminal, etc., may become a node in the blockchain system by joining the Peer-To-Peer network.

According to a further aspect of embodiments of the present invention, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.

Alternatively, in the present embodiment, the above-described computer-readable storage medium may be configured to store a computer program for executing the steps of:

acquiring streaming media data acquired by image acquisition equipment;

determining a key image according to the evaluation coefficient;

and sending the key image to the application client.

Alternatively, in this embodiment, it will be understood by those skilled in the art that all or part of the steps in the methods of the above embodiments may be performed by a program for instructing a terminal device to execute the steps, where the program may be stored in a computer readable storage medium, and the storage medium may include: flash disk, read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), magnetic or optical disk, and the like.

The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

The integrated units in the above embodiments may be stored in the above-described computer-readable storage medium if implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing one or more computer devices (which may be personal computers, servers or network devices, etc.) to perform all or part of the steps of the method of the various embodiments of the present invention.

In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In several embodiments provided in the present application, it should be understood that the disclosed client may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and are merely a logical functional division, and there may be other manners of dividing the apparatus in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims

1. A method for transmitting streaming media data, comprising:

acquiring streaming media data acquired by image acquisition equipment;

determining candidate images of each frame containing a face image area from the streaming media data;

cutting out an image area taking the face image area as an area center from the candidate image according to a target size corresponding to the acquisition resolution of the image acquisition device to obtain a target image, wherein cutting out the image area taking the face image area as the area center from the candidate image according to the target size corresponding to the acquisition resolution of the image acquisition device to obtain the target image comprises the following steps: determining hardware attribute information of the image acquisition equipment; acquiring a target size corresponding to the acquisition resolution of the image acquisition equipment according to the hardware attribute information; cutting the candidate image according to the target size to obtain a target image;

Transmitting target streaming media data formed by the target images to a background server;

receiving identity information of a target object sent by the background server, wherein the target object is used for indicating an object identified by the background server from the face image area of the target image;

and under the condition that the identity information of the target object reaches the verification condition, determining that the target object is a legal object.

2. The method according to claim 1, wherein the acquiring the target size corresponding to the acquisition resolution of the image acquisition device according to the hardware attribute information includes:

the method comprises the steps of obtaining model information of the image acquisition equipment in the hardware attribute information, wherein the model information corresponds to acquisition resolution of the image acquisition equipment one by one;

and acquiring the target size matched with the model information.

3. The method of claim 2, wherein the obtaining the target size that matches the model information comprises:

sending a configuration request carrying the model information to the background server;

and acquiring an image configuration parameter matched with the model information and returned by the background server in response to the configuration request, wherein the image configuration parameter is used for indicating the target size matched with the model information.

4. The method of claim 1, wherein cropping the candidate image according to the target size to obtain the target image comprises:

determining position coordinates of the region center of the face image region in the candidate image;

and cutting the candidate image according to the target size by taking the position coordinates as the circle center to obtain the target image comprising the face image area.

5. The method of claim 1, further comprising, after the acquiring the streaming media data acquired by the image acquisition device:

performing face detection on the image in the streaming media data through a face image detection model configured in an application client associated with the image acquisition equipment;

and under the condition that the current image contains the face image area, determining the current image as the candidate image.

6. A method for transmitting streaming media data, comprising:

acquiring a target image in target streaming media data sent by an application client, wherein the target image is an image area which is cut out from a candidate image and takes a face image area as an area center according to a target size corresponding to the acquisition resolution of image acquisition equipment, the target size is acquired according to hardware attribute information of the image acquisition equipment, the candidate image is an image which contains the face image area and is determined in the streaming media data acquired by the image acquisition equipment, and the application client has an association relation with the image acquisition equipment;

Respectively carrying out weighted fusion processing on the face symmetry characteristics, the face definition characteristics, the face illumination quality characteristics and the face image resolution characteristics corresponding to each target image to obtain the score of the picture quality corresponding to each target image;

determining the target image with the highest score of the picture quality as a key image;

sending the key image to the application client;

inputting the key images into a face recognition model to obtain a recognition result, wherein the face recognition model is a neural network model for recognizing face images after training by utilizing a plurality of sample images;

and determining the identity information of the target object displayed in the face image area of the key image according to the identification result.

7. The method of claim 6, further comprising, prior to the obtaining the target image in the target streaming media data sent by the application client:

receiving a configuration request sent by the application client, wherein the configuration request carries model information of the image acquisition equipment, and the model information corresponds to acquisition resolution of the image acquisition equipment one by one;

Responding to the configuration request, and acquiring a target image configuration parameter configured for the model information, wherein the target image configuration parameter is used for indicating the target size matched with the model information;

and sending the target image configuration parameters to the application client so that the application client cuts according to the target size to obtain the target image.

8. The method of claim 6, comprising, prior to the obtaining the target image in the target streaming media data sent by the application client:

setting image configuration parameters for image acquisition equipment of different types, wherein the types of the image acquisition equipment are in one-to-one correspondence with the acquisition resolutions of the image acquisition equipment, and the image configuration parameters are used for indicating cutting sizes matched with the types;

and storing the image configuration parameters into a background database.

9. A streaming media data transmission apparatus, comprising:

the first acquisition unit is used for acquiring the streaming media data acquired by the image acquisition equipment;

the clipping unit determines candidate images of each frame containing a face image area from the streaming media data; cutting out an image area taking the face image area as an area center from the candidate image according to a target size corresponding to the acquisition resolution of the image acquisition device to obtain a target image, wherein cutting out the image area taking the face image area as the area center from the candidate image according to the target size corresponding to the acquisition resolution of the image acquisition device to obtain the target image comprises the following steps: determining hardware attribute information of the image acquisition equipment; acquiring a target size corresponding to the acquisition resolution of the image acquisition equipment according to the hardware attribute information; cutting the candidate image according to the target size to obtain a target image;

A transmission unit, configured to transmit target streaming media data composed of the target image to a background server;

the first receiving unit is used for receiving the identity information of the target object sent by the background server, wherein the target object is used for indicating the object identified by the background server from the face image area of the target image;

and the first verification unit is used for determining that the target object is a legal object under the condition that the identity information of the target object reaches a verification condition.

10. A streaming media data transmission apparatus, comprising:

the image acquisition device comprises a first acquisition unit, a second acquisition unit and an image acquisition unit, wherein the first acquisition unit is used for acquiring a target image in target streaming media data sent by an application client, the target image is an image area which is cut out from a candidate image according to a target size corresponding to acquisition resolution of image acquisition equipment and takes a face image area as an area center, the target size is acquired according to hardware attribute information of the image acquisition equipment, the candidate image is an image of which each frame determined in streaming media data acquired by the image acquisition equipment contains the face image area, and the application client and the image acquisition equipment have an association relation;

The second acquisition unit is used for respectively carrying out weighted fusion processing on the face symmetry characteristics, the face definition characteristics, the face illumination quality characteristics and the face image resolution characteristics corresponding to each target image to obtain the score of the picture quality corresponding to each target image;

a determining unit, configured to determine the target image with the highest score of the picture quality as a key image;

a sending unit, configured to send the key image to the application client;

the identification unit is used for inputting the key images into a face identification model to obtain an identification result, wherein the face identification model is a neural network model for identifying face images after training by utilizing a plurality of sample images;

and the second determining unit is used for determining the identity information of the target object displayed in the face image area of the key image according to the identification result.

11. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the program when run performs the method of any one of claims 1 to 5 or the method of any one of claims 6 to 7.

12. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of the claims 1 to 5 or the method of any of the claims 6 to 7 by means of the computer program.