Image display control method, device and apparatus

Abstract

The application discloses an image display control method, device and equipment, and belongs to the technical field of image processing. The image display control method comprises the following steps: receiving a first input of a user on a target object node in an object relationship graph, the object relationship graph being a graph indicating the relationship between at least two objects, the object relationship graph comprising at least two object nodes, an object identifier being displayed on each object node, the object identifier being used for indicating an object, and a connection line being displayed between two objects having an object relationship; and in response to the first input, displaying at least one image containing a target object, the target object being an object indicated by a target object identifier displayed on the target object node.

Description

Technical Field

[0001] This application belongs to the field of image processing technology, specifically relating to an image display control method, apparatus, and device. Background Technology

[0002] With the widespread use of mobile phones and other terminal devices, users are increasingly using the camera function on these devices to take pictures, making the camera one of the most frequently used applications on these devices.

[0003] Due to users taking photos and saving images, terminal devices often store a large number of images. When users need to find and browse images of a specific object, they need to flip through all the images one by one, making it difficult for users to quickly find the image containing the specific object from a large number of images. Summary of the Invention

[0004] The purpose of this application is to provide an image display control method, apparatus, and device that enables users to quickly find images containing specific objects from a large number of images, thereby improving the convenience of image searching.

[0005] In a first aspect, embodiments of this application provide an image display control method, the method comprising:

[0006] Receive the user's first input on the target object node in the object relationship graph, the object relationship graph is a graph indicating the object relationship of at least two objects, the object relationship graph includes at least two object nodes, each object node displays an object identifier, the object identifier is used to indicate an object, and a connecting line is displayed between two objects that have an object relationship;

[0007] In response to the first input, at least one image containing the target object is displayed, the target object being the object indicated by the target object identifier displayed on the target object node.

[0008] Secondly, embodiments of this application provide an image display control device, the device comprising:

[0009] The receiving module is used to receive the user's first input on the target object node in the object relationship graph. The object relationship graph is a graph indicating the object relationship between at least two objects. The object relationship graph includes at least two object nodes. Each object node displays an object identifier, which is used to indicate an object. A connecting line is displayed between two objects that have an object relationship.

[0010] The display module is configured to, in response to the first input, display at least one image containing a target object, wherein the target object is the object indicated by the target object identifier displayed on the target object node.

[0011] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, wherein the memory stores programs or instructions executable on the processor, and the programs or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0012] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0013] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0014] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the method described in the first aspect.

[0015] In this embodiment, an object relationship graph is set up to indicate the relationship between at least two objects. Object identifiers are displayed on at least two object nodes within the object relationship graph, and connecting lines are displayed between the two objects with an object relationship. Upon receiving a user's first input on a target object node in the object relationship graph, at least one image containing the target object indicated by that target object node can be displayed. Since the object identifiers displayed on each object node in the object relationship graph indicate an object, and the relationship between the objects indicated by each object identifier can be intuitively displayed, the user only needs to select one object node, such as the target object node, to quickly find and display at least one image containing the target object. This facilitates the user's ability to quickly find images containing specific objects from a large number of images, improving the convenience of image searching. Attached Figure Description

[0016] Figure 1 This is a flowchart of an image display control method provided in some embodiments of this application;

[0017] Figure 2 This is a schematic diagram of a tree topology provided in some embodiments of this application;

[0018] Figure 3 This is a schematic diagram of a mesh topology provided in some embodiments of this application;

[0019] Figure 4These are schematic diagrams illustrating display methods for foldable screen electronic devices provided in some embodiments of this application;

[0020] Figure 5(a) is a schematic diagram of a map display method based on a flat screen electronic device provided in some embodiments of this application;

[0021] Figure 5(b) is a schematic diagram of an image display method based on a flat-screen electronic device provided in some embodiments of this application;

[0022] Figure 6 This is a flowchart of an image display control method provided in some embodiments of this application;

[0023] Figure 7 These are schematic diagrams illustrating object recognition results provided by some embodiments of this application;

[0024] Figure 8 This is a schematic diagram of object marking results provided by some embodiments of this application;

[0025] Figure 9 This is a structural block diagram of an image display control device provided in some embodiments of this application;

[0026] Figure 10 These are structural block diagrams of electronic devices provided in some embodiments of this application;

[0027] Figure 11 A schematic diagram of the hardware structure of an electronic device provided to implement some embodiments of this application. Detailed Implementation

[0028] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0029] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, there may be one or more target objects, with "more" referring to at least two. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0030] The image display control method, apparatus, device, and storage medium provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0031] The image display control method provided in this application can be applied to image browsing scenarios. The following section combines... Figures 1-8 The image display control method provided in the embodiments of this application will be described in detail. It should be noted that the image display control method provided in the embodiments of this application can be executed by an image display control device. In this embodiment, the image display control method is illustrated using an image display control device executing the image display control method as an example.

[0032] Figure 1 This is a flowchart of an image display control method provided in one embodiment of this application.

[0033] like Figure 1 As shown, the image display control method includes at least the following steps: Steps 110-140, which will be described in detail below.

[0034] Step 110: Receive the user's first input on the target object node in the object relationship graph. The object relationship graph is a graph that indicates the object relationship between at least two objects. The object relationship graph includes at least two object nodes. Each object node displays an object identifier, which is used to indicate an object. A connecting line is displayed between two objects that have an object relationship.

[0035] In some embodiments of this application, the object relationship graph can be a graph that a user retrieves and displays from the program interface of an image storage application. The image storage application can be, for example, a photo album app, a gallery app, a camera app, or image processing software. The object relationship graph can include nodes corresponding to multiple objects, i.e., object nodes. Each object node can be displayed as an object identifier corresponding to the corresponding object, and connecting lines are displayed between object nodes corresponding to objects with object relationships.

[0036] Furthermore, the identifiers in this application are text, symbols, images, etc., used to indicate information, and can use controls or other containers as carriers for displaying information, including but not limited to text identifiers, symbol identifiers, and image identifiers. Among them, the object identifier can be information that can uniquely represent the object, specifically including at least one of the following: object image, object name, and object symbol.

[0037] In some embodiments of this application, the object may include at least one of the following: person, object, animal, scenery; correspondingly, the object relationship may include at least one of the following: person relationship, affiliation relationship, organization relationship.

[0038] When the object is a person, the object identifier is specifically a person identifier, which includes at least one of the following: a person image, a person name, or a person symbol. When the object is an object, the object identifier is specifically an object identifier, which includes at least one of the following: an object image, an object name, or an object symbol. When the object is an animal, the object identifier is specifically an animal identifier, which includes at least one of the following: an animal image, an animal name, or an animal symbol. When the object is a landscape, the object identifier is specifically a landscape identifier, which includes at least one of the following: a landscape image, a landscape name, or a landscape symbol.

[0039] Here, animals can include, for example, cats and dogs; objects can include, for example, tables, chairs, and appliances; and scenery can include, for example, mountains, trees, and waterfalls.

[0040] In this way, since the object can be a person, an object, an animal, or a landscape, users can quickly and easily find images of any type of object by selecting object nodes in the object relationship graph, thereby improving the convenience for users to find specific images containing a certain type of object.

[0041] In addition, interpersonal relationships can be the relationships between people, belonging relationships can be the relationships between people and things, and organizational relationships can be the organizational structure relationships of an enterprise.

[0042] Taking character relationships as an example, multiple character nodes can be displayed in the object relationship graph. Each character node displays a character image to indicate the character corresponding to that image. Two characters with an object relationship are connected by a line. Thus, the object relationship graph can more intuitively represent the relationships between characters.

[0043] Taking attribution relationships as an example, multiple person nodes and object nodes can be displayed in the object relationship graph. Each person node displays a person image to indicate the person to which the image belongs, and each object node displays an object image to indicate the object to which the image belongs. Connecting lines are displayed between people and objects with object relationships. Thus, the object relationship graph can more intuitively represent the attribution relationships between each person and each object.

[0044] Taking organizational relationships as an example, multiple enterprise nodes can be displayed in the object relationship graph. Each enterprise node displays an enterprise name to indicate the corresponding enterprise. Two enterprises with an object relationship are connected by a line. Thus, the object relationship graph can more intuitively represent the organizational relationships between various enterprises.

[0045] In addition, in some possible implementations, prior to step 110 above, the image display control method provided in this application may further include: displaying an object relationship map.

[0046] For example, an object relationship graph can be represented in the form of a tree topology graph, or in the form of a star topology graph or a network topology graph.

[0047] Taking the object relationship as a person relationship as an example, in some specific examples, such as Figure 2 As shown, a tree-like topology diagram can be displayed to indicate the relationships between characters. Each node in the tree-like topology diagram displays a character identifier for each character, which may include a character image and a character name. For example, node 21 displays "Father" and its corresponding avatar, and node 22 displays "Mother" and its corresponding avatar.

[0048] In other examples, such as Figure 3 As shown, a mesh topology diagram can be displayed to indicate the relationships between characters. Each node in the mesh topology diagram can display a character identifier, which may specifically include character images, such as the father's image displayed at node 31 and the mother's image displayed at node 32.

[0049] In addition, the target object can be an object contained in the image that the user wants to find, where the target object node can be a node in the object relationship graph that indicates the target object.

[0050] In some embodiments of this application, when a user needs to search for an image containing a target object in a photo album, the aforementioned first input can be used to select the node corresponding to the target object the user wants to find, i.e., the target object node. The first input can be a first operation. Exemplarily, the aforementioned first input includes, but is not limited to: the user clicking on the target object node in the object relationship graph using a touch device such as a finger or stylus, or a voice command input by the user, or a specific gesture input by the user, or other feasible inputs. The specific input can be determined according to actual usage needs, and the embodiments of this invention do not limit it. The specific gesture in the embodiments of this application can be any one of a single-click gesture, a swipe gesture, a drag gesture, a pressure recognition gesture, a long-press gesture, an area change gesture, a double-press gesture, or a double-tap gesture; the click input in the embodiments of this application can be a single-click input, a double-tap input, or a click input of any number of times, and can also be a long-press input or a short-press input.

[0051] For example, the first input mentioned above could be: a user clicking on the object identifier displayed on the target object node in the object relationship graph using their finger. Alternatively, the first input could be: a voice command issued by the user to the electronic device displaying the object relationship graph, indicating selection of the target object node. Another possible first input could be: a user moving a selection box in the object relationship graph using a swipe gesture, and then confirming selection of the target object node by clicking when the selection box stops on the desired target object node.

[0052] Step 120: In response to the first input, display at least one image containing the target object, which is the object indicated by the target object identifier displayed on the target object node.

[0053] The images in this application can be static or animated, and their formats include, but are not limited to, jpg, jpeg, bmp, tif, gif, png, etc.

[0054] In some embodiments of this application, an electronic device may pre-store multiple images, such as multiple images stored in a photo album. The electronic device may be a mobile phone, computer, tablet, or other device capable of storing and displaying images. These multiple images may include images taken by the user, or images downloaded and saved by the user from the network or applications, without limitation. Furthermore, each image may include one or more objects.

[0055] Furthermore, the final image to be displayed in this application is determined based on the target object node selected by the user.

[0056] For example, when a user clicks on a target object node in the object relationship graph, one or more images containing the target object corresponding to that node can be found from a stored list of images and displayed. Thus, by selecting a target object node in the object relationship graph, at least one image containing the target object indicated by that node can be displayed, allowing users to quickly locate the image of the object they are looking for, narrowing the image search range, and thus facilitating the rapid finding of images of specific objects.

[0057] In other embodiments of this application, when a user clicks to select two target object nodes in the object relationship graph, one or more group photos containing both target objects corresponding to the two nodes can be found from a stored collection of images and displayed. Thus, by selecting multiple target object nodes in the object relationship graph, at least one group photo containing the multiple target objects indicated by those nodes can be displayed, allowing users to quickly locate the group photo of the multiple objects they need to find, narrowing the image search range, and thus facilitating the user to quickly find group photos of specific multiple objects.

[0058] Therefore, by displaying an object relationship graph indicating the relationship between at least two objects, and displaying object identifiers on at least two object nodes included in the object relationship graph, with connecting lines between the two objects that have an object relationship, upon receiving the user's first input on a target object node in the object relationship graph, at least one image containing the target object indicated by that target object node can be displayed. In this way, the object relationship graph can intuitively show the relationships between the objects indicated by each object identifier, allowing users to quickly find images of any one or more objects by using the first input on any object node in the object relationship graph, thus facilitating the user to quickly find images containing specific objects from a large number of images.

[0059] Based on this, in some embodiments of this application, if the electronic device displays such as Figure 2 The diagram shown contains eight characters: myself, my younger brother, my father, my mother, my grandfather, my grandmother, my maternal grandfather, and my maternal grandmother. My brother and I are siblings; my father and I are father and daughter; my mother and I are mother and daughter; my brother and father are father and son; my brother and mother are mother and son; my father and mother are husband and wife; my father and grandfather are father and son; my father and grandmother are mother and son; my grandfather and grandmother are husband and wife; my mother and grandfather are father and daughter; my mother and grandmother are mother and daughter; and my maternal grandfather and grandmother are husband and wife. When a user needs to find an image of their father, they can follow the steps below. Figure 4 As shown, by clicking on the object node 401 that indicates the father, all images 42 containing the father are found and displayed.

[0060] In addition, in some other embodiments of this application, if the electronic device displays something like... Figure 2 The diagram shows the relationships between people. If the user needs to find the image of the mother, then similarly, the user can click on the object node 22 that indicates the mother to find and display all images containing the mother.

[0061] The image display control method of this application is applicable to electronic devices with various display screen types. Specifically, the electronic devices to which the image display control method of this application is applicable include, but are not limited to, flat-screen electronic devices, curved-screen electronic devices, and foldable-screen electronic devices. The display screen of a flat-screen electronic device is flat, the edge of the display screen of a curved-screen electronic device is arc-shaped, and the display screen of a foldable-screen electronic device can be folded. Furthermore, different methods can be used for image display on electronic devices with different display screen types.

[0062] For example, for electronic devices with foldable screens, in some embodiments, before step 110 above, the image display control method provided in this application embodiment may further include:

[0063] Display the object relationship graph in the first screen area;

[0064] Accordingly, step 120 above may specifically include:

[0065] Display at least one image containing the target object in the second screen area.

[0066] Here, the first screen area and the second screen area can be areas within different displays, or they can be different areas within the same display. For example, the first screen area and the second screen area can be two different displays in a foldable electronic device, or they can be different display areas of the same display after it is unfolded; there is no limitation here. The foldable screen can be a flexible screen, or it can be a foldable screen with a rotating axis in the middle or at the edges.

[0067] In some embodiments of this application, such as Figure 4 As shown, a tree topology diagram 41 can be displayed on the left side of the foldable screen electronic device. If the user clicks and selects the object node 401 in the tree topology diagram 41 that indicates the parent, the image containing the parent can be found from multiple stored images, and all the images 42 containing the parent found can be displayed on the right side of the foldable screen electronic device.

[0068] In this way, by displaying an object relationship graph in the first screen area and an image of the target object indicated by the target object node selected by the user in the second screen area, users can easily switch between images of different objects at any time based on the object relationship graph. This also makes full use of the display area of ​​the foldable screen electronic device and improves the utilization rate of the display area in the foldable screen.

[0069] In some embodiments of this application, for electronic devices with ordinary displays, before step 110 above, the image display control method provided in the embodiments of this application may further include:

[0070] Display the object relationship graph on the target interface;

[0071] Accordingly, step 120 above may specifically include:

[0072] Display at least one image containing the target object in a floating window, wherein the floating window is displayed on the target interface.

[0073] Here, the target interface can be any interface displayed on an electronic device, which can be an interface in any application, and the floating window can be a window that floats on the target interface.

[0074] In some embodiments of this application, as shown in FIG5(a), a tree topology diagram 51 can be displayed in the interface 50 of a flat-screen electronic device. If the user clicks to select an object node 501 in the tree topology diagram 51, and the object identifier displayed on the object node 501 indicates that the object is the parent, then the image containing the parent can be found from multiple stored images, and all the images containing the parent found can be displayed in the floating window 52 shown in FIG5(b).

[0075] In this way, by displaying the object relationship graph in the target interface and the image of the target object indicated by the target object node selected by the user in the floating window, more information can be displayed using limited screen resources, and users can easily switch between images of different objects at any time based on the object relationship graph.

[0076] In addition, in some embodiments, before step 110 above, the image display control method provided in this application may further include, as follows: Figure 6 The steps shown are: Steps 610-640, which will be explained in detail below.

[0077] Step 610: Perform object recognition on at least two reference images to obtain at least two objects.

[0078] Here, the reference image can be an image pre-stored in the electronic device, including but not limited to images taken by the user, and images downloaded and saved by the user from the network or an application. Furthermore, different recognition technologies can be used for object recognition depending on the type of object. For example, facial recognition technology can be used when the object is a person; object recognition technology can be used when the object is an object; biometric technology can be used when the object is an animal; and image feature recognition technology can be used when the object is a landscape.

[0079] For example, object recognition can be performed on multiple reference images stored in an electronic device, and the same object can be clustered to obtain multiple different objects. Taking a person as an example, face recognition can be performed on multiple images in a mobile phone, and the same person can be clustered to obtain multiple different people.

[0080] Step 620: Obtain the object relationship between at least two objects.

[0081] In some embodiments of this application, the object relationships between objects can be configured by the user or automatically identified, and are not limited here.

[0082] Based on this, in some embodiments, when the object includes a person and the object relationship includes a person relationship, step 620 above may specifically include:

[0083] Extract at least two face images from at least two reference images, wherein the at least two face images are face images of different people;

[0084] Receive user input of a label for the target face image from at least two extracted face images. The label input is used to input the name of the person.

[0085] In response to the labeled input, the person corresponding to the target face image is identified as the reference person;

[0086] Receive user-labeled input for other extracted facial images; the label input is used to input the names of the people.

[0087] In response to the labeled input, the relationship between the person in each face image and the reference person is determined based on the person's name entered in the labeled input.

[0088] Here, the face image can be an image containing a person's face extracted from a reference image. Different face images can be extracted for different people, meaning the extracted face images are face images of different people. The face image extraction method can be to find the contour of the face region in the image based on multiple preset facial feature points, and then crop the image corresponding to that contour.

[0089] For example, based on the reference image corresponding to each person, if there is only one reference image containing a certain person, the image of the person's face can be directly extracted from that reference image to obtain the person's face image. If there are multiple reference images containing a certain person, a target reference image can be determined from the multiple reference images corresponding to that person, and then the image of the person's face can be extracted from the target reference image to obtain the person's face image. The target reference image can be an image randomly selected from the multiple reference images containing that person, or a recently stored image from the multiple reference images containing that person, or it can be the image with the best image quality selected from the reference images containing that person according to a preset selection rule. Here, the preset selection rule can include at least one of the following: optimal lighting, minimum facial angle, and highest clarity.

[0090] For example, such as Figure 7 As shown, if four people are identified from multiple reference images, then the facial images 70 corresponding to these four people can be displayed. These facial images 70 can be obtained by selecting the image with the best image quality from the reference images corresponding to each person, and then cropping that image. The image with the best image quality could be, for example, the image with the best lighting on the person's face, the image with the smallest facial skew angle, or the image with the highest facial clarity.

[0091] Additionally, the tagging input can be an input that adds a person's name to the facial images corresponding to each person. This input can be, for example, entered via an input method keyboard or selected from a set of preset name tags. Different names can correspond to different relationships between people. Based on this, after the user enters a name, the relationships between the people corresponding to the tagged facial images can be determined.

[0092] In some specific examples, users can base on Figure 7 The displayed facial images are labeled with individual people, for example, such as... Figure 8 As shown, we can first label "I" and determine the person corresponding to the face image 81 labeled "I" as the reference person. Then, we can label the other face images, labeling face image 82 as "father," face image 83 as "mother," and face image 84 as "younger brother." In this way, the system can automatically determine the relationship between the person corresponding to each face image and the reference person based on the person's name labeled on each face image. For example, after labeling "father," "mother," and "I," we can determine the father-son relationship between "father" and "I," the mother-son relationship between "mother" and "I," and the husband-wife relationship between "father" and "mother," etc.

[0093] Furthermore, after determining the object relationships between each object, an object relationship graph can be constructed with objects as nodes and the object relationships between objects as connecting lines. The adjacency matrix corresponding to this object relationship graph can then be determined. The object relationships between each object can then be stored in the adjacency matrix. Of course, a mapping table can also be used to store the object relationships between each object; this is not a limitation here.

[0094] In this way, by having users add tags to the facial images corresponding to the identified people, the relationships between each tagged person can be accurately determined. This allows for the construction of an object relationship graph based on these relationships in subsequent steps, as well as the display of the corresponding images.

[0095] Step 630: Obtain object information for at least two objects. The object information includes at least one of the following: object image, object name, and object relationship terminology.

[0096] Here, when the object is a person, the object image can be, for example, a face image, the object name can be, for example, a person's name, and the object relationship title can be, for example, a title related to the relationship between the people, such as father or mother.

[0097] For example, object information can be obtained from user input or indirectly obtained based on user input; no limitation is made here.

[0098] It should be noted that step 630 can be executed after step 620, before step 620, or simultaneously with step 620. This application does not limit this.

[0099] Step 640: Generate an object relationship graph based on the object relationship between at least two objects and the object information of at least two objects.

[0100] Here, the object relationship graph may include object nodes corresponding to multiple objects. Each object node may display object information indicating the object. Object nodes corresponding to objects with object relationships are connected by lines.

[0101] In some embodiments of this application, such as Figure 2 As shown, in addition to displaying the object image of the indicated object on the object node, the object relationship name can also be displayed below the object image. For example, "Father" is displayed below the face image 21 displayed on the parent node, and "Mother" is displayed below the face image 22 displayed on the mother node.

[0102] In other embodiments of this application, such as Figure 3As shown, in addition to displaying the object image of the indicated object on the object node, the relationship information between the objects indicated by the two object nodes can also be displayed on the connection line. For example, "couple" is displayed on the connection line between object node 31 and object node 32, and "father and child" is displayed on the connection line between object node 31 and object node 33.

[0103] In addition, after users have labeled each face image, they can manually trigger the generation of an object relationship graph.

[0104] For example, such as Figure 8 The interface shown also displays a function control for triggering the generation of an object relationship graph, namely the "Generate Relationship Graph" control 85. After adding tags, the user can click on the control 85 to trigger the generation of the corresponding object relationship graph.

[0105] In this way, by identifying the objects contained in the reference image and obtaining the object relationships between them, an object relationship graph is generated, with objects as nodes and the object relationships between objects as connecting lines. This object relationship graph allows users to intuitively understand the object relationships between various objects, making it easier for them to quickly locate the image containing the specific object they want to find and browse, thus reducing the difficulty for users to quickly find images of specific objects from a large number of images.

[0106] Furthermore, when the object includes characters, the object relationship includes character relationships, and at least two reference images are stills from the target drama, the at least two reference images may include N characters from the drama, where N is an integer greater than 1. Based on this, in some embodiments, step 620 above may specifically include:

[0107] Obtain information about the target play related to N characters, including at least one of the following: play title and character introductions for the N characters.

[0108] Based on the information in the play, determine the relationships between N characters in the play.

[0109] Here, the target script type includes, but is not limited to, TV series, movies, plays, novels, etc.

[0110] For example, by identifying characters from a still image, information about the target drama related to those characters can be retrieved from data loaded locally or from the internet. This information includes, but is not limited to, the drama's title and character descriptions. By extracting relationship information between the characters from this information, the relationships between them can be determined.

[0111] For example, by identifying characters in stills from a target film or television drama, one can search online for relevant information about the target film or television drama corresponding to those characters, such as the title of the film or television drama, introductions of the characters in the film or television drama, etc. From the introductions of the characters, the relationships between the characters in the film or television drama can be extracted.

[0112] For example, by identifying the characters in the illustrations of the target novel, one can search the internet for relevant information about the target novel corresponding to those characters, such as the novel's title and introductions of each character. From the introductions of each character, the relationships between the characters can be extracted.

[0113] In this way, by obtaining the relevant information about the characters in the play as shown in the image, the relationships between multiple characters can be automatically extracted, so as to construct an object relationship graph for these multiple characters.

[0114] Furthermore, when images of characters from the play are missing from multiple reference images, the images corresponding to the missing characters can be downloaded from the network based on the obtained play information, and their facial images can be extracted. Based on the relationships between the characters in the target play, an object relationship graph corresponding to the target play is generated and displayed. This object relationship graph can be a graph with the facial images corresponding to the characters in the target play as nodes and the object relationships between the characters as connecting lines.

[0115] In this way, by completing the character images, users can easily view the relationships between the characters in the target drama, and also easily view and browse the images corresponding to each character.

[0116] In addition, in some implementations, besides obtaining script information online from the network and identifying the relationships between characters in the script through script information, it is also possible to automatically identify the relationships between characters in the article by importing articles, generate a corresponding relationship graph based on the relationships, and then display the images corresponding to each character based on the relationship graph. The display method is the same as before and will not be described again here.

[0117] Furthermore, in some embodiments, prior to step 610 described above, the following steps are also included:

[0118] Classify at least two reference images according to at least two image classification dimensions to obtain an image set corresponding to at least two image types under each image classification dimension. The image classification dimensions include at least one of time, theme, location, event, and person.

[0119] Based on this, step 620 above may specifically include:

[0120] For each image set corresponding to each image type under each image classification dimension, establish the object relationship between at least two objects contained in at least two reference images in each image set;

[0121] One of the image classification dimensions corresponds to the generation of an object relationship graph.

[0122] For example, when the image classification dimension includes time, reference images can be classified according to their capture time, grouping reference images captured within the same time period into one image set. For instance, reference images captured in 2021 can be grouped into one image set, and reference images captured in 2022 into another. In this way, object relationships can be established between different objects contained within each reference image in an image set, creating connections between object nodes corresponding to any two objects in that image set. Furthermore, images captured each year can be treated as a large node, connected to nodes corresponding to images captured in the previous year and those captured in the following year. This generates an object relationship graph corresponding to the time dimension.

[0123] In some embodiments of this application, when the preset dimension includes a theme, for example, multiple stored reference images can be classified according to themes such as tourism, sports, and spring outings. Taking sports as an example, such as the theme of basketball, the objects contained in all reference images under this theme are listed, and new object relationships are generated between different objects based on the theme of basketball. In this way, an object relationship map corresponding to the theme dimension can be generated.

[0124] In some embodiments of this application, when the image classification dimension includes location, the reference images can be classified according to their shooting location. Reference images taken within the same location area can be grouped into one image set. For example, reference images taken within City A can be grouped into one image set, and reference images taken within City B can be grouped into another. In this way, object relationships can be established between different objects contained within each reference image in an image set; that is, object relationships can be established between objects that have visited the same location, thus creating a connection between the object nodes corresponding to any two objects in the image set. This generates an object relationship map corresponding to the location dimension.

[0125] In some embodiments of this application, when the preset dimension includes events, the reference images can be classified according to the events recorded in them, grouping reference images recording the same events into one image set. For example, reference images recording wedding events can be grouped into one image set, and reference images recording conference events can be grouped into another image set. In this way, object relationships can be established between different objects contained within each reference image in an image set; that is, object relationships can be established between objects that have experienced the same event, thus creating a connection between the object nodes corresponding to any two objects in the image set. This generates an object relationship graph corresponding to the event dimension.

[0126] In some embodiments of this application, when the preset dimension includes people, multiple stored reference images can be categorized according to the emotional themes of the people, such as the theme of joy, anger, sorrow, and happiness. For example, if the theme is joy, the objects contained in all reference images under this theme are listed, and new object relationships are generated between different objects based on the theme of joy. In this way, an object relationship map corresponding to the dimension of people can be generated.

[0127] In addition, reference images can be classified according to image classification dimensions containing two or more factors, thereby generating an object relationship graph.

[0128] Based on this, in some embodiments of this application, when the image classification dimension includes time and location, the reference images can be classified according to their shooting time and location. Reference images taken within the same time period and location area can be grouped into one image set. For example, all reference images taken in City A in 2021 can be grouped into one image set, and all reference images taken in City B in 2022 can be grouped into another image set. In this way, object relationships can be established between different objects contained within each reference image in an image set. That is, new object relationships can be established between objects that have visited the same location within the same time period, so that a connection line can be established between the object nodes corresponding to any two objects in the image set. Thus, an object relationship map corresponding to the dimensions including both time and location can be generated.

[0129] In other embodiments of this application, when the image classification dimension includes events and people, the reference images can be classified according to the events and expressions of the people recorded in the reference images. Reference images with the same expressions of people under the same event are grouped into one image set. For example, all reference images with joyful expressions in a wedding event are grouped into one image set, and all reference images with sad expressions in a wedding event are grouped into another image set. In this way, object relationships can be established between different objects contained in each reference image in an image set. That is, new object relationships can be established between people with the same expressions in the same event, so as to establish a connection between the object nodes corresponding to any two people in the image set. In this way, an object relationship map corresponding to the two factors of events and people can be generated.

[0130] In this way, by classifying images from multiple preset dimensions and establishing object relationships between different objects contained in each reference image within the image set corresponding to each image category, different object relationship maps can be generated from different perspectives. Users can select object relationship maps of various dimensions to browse images, thereby enhancing the fun of the image browsing process.

[0131] Furthermore, when there are at least two images containing the target object, in some implementations, step 120 may specifically include:

[0132] Identify at least two age groups corresponding to the target object in at least two images containing the target object;

[0133] Based on at least two age groups corresponding to the target object in at least two images, cluster the at least two images to obtain the image corresponding to each age group;

[0134] Display images corresponding to at least two age groups in chronological order.

[0135] Here, to further facilitate users in finding images of a specific object at a specific age, we can determine the age range of the target object in each image containing the target object, cluster the images of the target object at the same age range, and then obtain the images corresponding to the target object at different age ranges.

[0136] For example, the methods for determining the age group of the target object in each image include, but are not limited to, obtaining the shooting time of the image and using the correspondence between the shooting time and the various age groups of the target object to determine the age group of the target object corresponding to the shooting time of each image. Of course, an age group recognition model can also be constructed to identify the age group of the target object in the image, thereby estimating the age group of the target object in each image.

[0137] In some specific examples, multiple images can be categorized according to the target person's age group, such as two years per age group, three years per age group, and the images of the target person corresponding to different age groups can be arranged and displayed according to age group based on the time sequence between each age group.

[0138] In this way, by arranging and displaying multiple images containing the target object according to different age groups of the target object, it is easier for users to find images of a specific object in a specific age group, thereby further reducing the difficulty for users to quickly find specific images from a large number of images.

[0139] Furthermore, in some other embodiments, the image display control method provided in this application may also include:

[0140] Receive the user's second input for M object nodes in the object relationship graph, where M is an integer greater than 1; the M object identifiers displayed on the M object nodes indicate the M objects;

[0141] In response to the second input, if a group photo containing M objects is available, the group photo image is displayed;

[0142] In response to the second input, if there is no group photo containing M objects, output a prompt message. The prompt message is used to inform the user that there is no group photo containing M objects and to prompt the user to take a group photo containing M objects.

[0143] Here, the second input can be the user's selection of multiple object nodes in the object relationship graph. The input method for this selection includes, but is not limited to, single click, double click, long press, etc.

[0144] For example, if a user selects multiple object nodes in an object relationship graph simultaneously, a group photo image containing all the objects indicated by the selected object nodes can be displayed. Alternatively, if no group photo image containing the selected objects exists among the multiple reference images stored in the electronic device's database, a corresponding prompt message can be output to inform the user that the group photo image does not exist and to prompt the user to take a group photo image containing the selected objects. The output method of the prompt message includes, but is not limited to, text and image display, sound prompts, vibration prompts, and any combination thereof, and is not limited here.

[0145] In this way, by simultaneously selecting M object nodes in the object relationship graph, a group photo image containing the objects indicated by the M object nodes is displayed, which makes it easy for users to quickly find images containing multiple specific objects, thereby further reducing the difficulty for users to quickly find specific images from a large number of images.

[0146] It should be noted that the application scenarios described in the above embodiments of this disclosure are for the purpose of more clearly illustrating the technical solutions of the embodiments of this disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of this disclosure. As those skilled in the art will know, with the emergence of new application scenarios, the technical solutions provided by the embodiments of this disclosure are also applicable to similar technical problems.

[0147] Based on the same inventive concept, this application also provides an image display control device. The following is in conjunction with... Figure 9 The image display control device provided in the embodiments of this application will be described in detail.

[0148] Figure 9 This is a structural block diagram of an image display control device provided in one embodiment of this application.

[0149] like Figure 9 As shown, the image display control device 700 may include:

[0150] The receiving module 701 is used to receive the first input from the user to the target object node in the object relationship graph. The object relationship graph is a graph indicating the object relationship between at least two objects. The object relationship graph includes at least two object nodes. Each object node displays an object identifier. The object identifier is used to indicate an object. A connecting line is displayed between two objects that have an object relationship.

[0151] Display module 702 is configured to display at least one image containing a target object in response to the first input, wherein the target object is the object indicated by the target object identifier displayed on the target object node.

[0152] The image display control device 600 described above will be described in detail below:

[0153] In one embodiment, the display module 702 is further configured to:

[0154] Display the object relationship graph before receiving the user's first input on the target object node in the object relationship graph;

[0155] The objects include at least one of the following: people, objects, animals, and landscapes;

[0156] The object relationships include at least one of the following: person relationship, affiliation relationship, and organizational relationship.

[0157] In one embodiment, the image display control device 700 further includes:

[0158] The recognition module is used to perform object recognition on at least two reference images to obtain at least two objects;

[0159] The acquisition module is used to acquire the object relationship between the at least two objects and to acquire the object information of the at least two objects, wherein the object information includes at least one of the following: object image, object name, and object relationship name;

[0160] The generation module is used to generate an object relationship graph based on the object relationship between the at least two objects and the object information of the at least two objects.

[0161] In one embodiment, the object includes a person, and the object relationship includes a person relationship;

[0162] The acquisition module is specifically used for:

[0163] Extract at least two face images from the at least two reference images, wherein the at least two face images are face images of different people;

[0164] Receive user input of a label for the target face image in at least two extracted face images, the label input being used to input the person's name;

[0165] In response to the labeled input, the person corresponding to the target face image is identified as the reference person;

[0166] Receive user annotation input for other extracted facial images, the annotation input being used to input the person's name;

[0167] In response to the labeled input, the relationship between the person corresponding to each face image and the reference person is determined based on the person name entered in the labeled input.

[0168] In one embodiment, the object includes characters, and the at least two reference images are stills from the target play; the at least two reference images include N characters from the play; N is an integer greater than 1;

[0169] The acquisition module is further specifically used for:

[0170] Obtain the drama information related to the N characters in the target drama, wherein the drama information includes at least one of the following: drama title, character introduction information of the N characters;

[0171] Based on the information about the play, determine the relationships between the N characters in the play.

[0172] In one embodiment, the image display control device 700 further includes:

[0173] The classification module is used to classify the at least two reference images according to at least two image classification dimensions before performing object recognition on at least two reference images to obtain at least two objects, thereby obtaining an image set corresponding to at least two image types under each image classification dimension, wherein the image classification dimension includes at least one of time, theme, location, event, and person;

[0174] The acquisition module is further specifically used for:

[0175] For each image set corresponding to each image type under each image classification dimension, establish the object relationship between at least two objects contained in at least two reference images in each image set;

[0176] One of the image classification dimensions corresponds to the generation of an object relationship graph.

[0177] In one embodiment, the display module 902 is further configured to:

[0178] Before receiving the user's first input on the target object node in the object relationship graph, the object relationship graph is displayed in the first screen area; and...

[0179] At least one image containing the target object is displayed in the second screen area; wherein the first screen area and the second screen area are areas on different displays, or the first screen area and the second screen area are different areas on the same display.

[0180] In one embodiment, the display module 902 is further configured to:

[0181] Before receiving the user's first input on the target object node in the object relationship graph, display the object relationship graph in the target interface; and,

[0182] Display at least one image containing the target object in a floating window, wherein the floating window is displayed on the target interface.

[0183] In one embodiment, when the number of images containing the target object is at least two, the display module 902 is specifically used for:

[0184] Identify at least two age groups corresponding to the target object in at least two images containing the target object;

[0185] Based on at least two age groups corresponding to the target object in the at least two images, the at least two images are clustered to obtain an image corresponding to each age group;

[0186] Display the images corresponding to the at least two age groups in chronological order.

[0187] In one embodiment, the receiving module 901 is further configured to:

[0188] Receive a second input from the user for M object nodes in the object relationship graph, where M is an integer greater than 1; the M object identifiers displayed on the M object nodes indicate the M objects;

[0189] The display module 902 is also used for:

[0190] In response to the second input, if a group photo containing the M objects exists, the group photo image is displayed;

[0191] In response to the second input, if there is no group photo image containing the M objects, a prompt message is output. The prompt message is used to inform the user that there is no group photo image containing the M objects and to prompt the user to take a group photo image containing the M objects.

[0192] Therefore, by setting up an object relationship graph to indicate the object relationships between at least two objects, and displaying object identifiers on at least two object nodes included in the object relationship graph, with connecting lines displayed between the two objects that have an object relationship, upon receiving the user's first input on a target object node in the object relationship graph, at least one image containing the target object indicated by that target object node can be displayed. In this way, the object relationship graph can intuitively display the relationships between the objects indicated by each object identifier, allowing users to quickly find the image of any object by using the first input on any object node in the object relationship graph, thus facilitating users to quickly find images containing specific objects from a large number of images.

[0193] The image display control device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the device.

[0194] The image display control device in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit it.

[0195] The image display control device provided in this application embodiment can achieve... Figures 1 to 8 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0196] Optional, such as Figure 10 As shown, this application embodiment also provides an electronic device 1000, including a processor 1001 and a memory 1002. The memory 1002 stores a program or instructions that can run on the processor 1001. When the program or instructions are executed by the processor 1001, they implement the various steps of the above-described image display control method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0197] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0198] Figure 11 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application.

[0199] The electronic device 1100 includes, but is not limited to, components such as: radio frequency unit 1101, network module 1102, audio output unit 1103, input unit 1104, sensor 1105, display unit 1106, user input unit 1107, interface unit 1108, memory 1109, and processor 1110.

[0200] Those skilled in the art will understand that the electronic device 1100 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 1110 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 10 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0201] The user input unit 1107 is used to receive the first input from the user to the target object node in the object relationship graph. The object relationship graph is a graph indicating the object relationship between at least two objects. The object relationship graph includes at least two object nodes. Each object node displays an object identifier. The object identifier is used to indicate an object. A connecting line is displayed between two objects that have an object relationship.

[0202] Display unit 1106 is configured to display at least one image containing a target object in response to the first input, wherein the target object is the object indicated by the target object identifier displayed on the target object node.

[0203] Therefore, by setting up an object relationship graph to indicate the object relationships between at least two objects, and displaying object identifiers on at least two object nodes included in the object relationship graph, with connecting lines displayed between the two objects that have an object relationship, upon receiving the user's first input on a target object node in the object relationship graph, at least one image containing the target object indicated by that target object node can be displayed. In this way, the object relationship graph can intuitively display the relationships between the objects indicated by each object identifier, allowing users to quickly find the image of any object by using the first input on any object node in the object relationship graph, thus facilitating users to quickly find images containing specific objects from a large number of images.

[0204] Optionally, display unit 1106 is also used to display an object relationship graph;

[0205] Optionally, the processor 1110 is configured to perform object recognition on at least two reference images to obtain at least two objects; obtain the object relationship between the at least two objects; obtain object information of the at least two objects, the object information including at least one of the following: object image, object name, object relationship terminology; and generate an object relationship graph based on the object relationship between the at least two objects and the object information of the at least two objects.

[0206] Optionally, the processor 1110 is further configured to extract at least two face images from the at least two reference images, wherein the at least two face images are face images of different people;

[0207] The user input unit 1107 is also used to receive a user's label input for the target face image in at least two extracted face images, the label input being used to input the person's name;

[0208] The processor 1110 is also configured to, in response to the labeled input, determine the person corresponding to the target face image as a reference person;

[0209] The user input unit 1107 is also used to receive user annotation input for other face images that have been extracted, wherein the annotation input is used to input the name of the person;

[0210] The processor 1110 is also configured to, in response to the marked input, determine the relationship between the person corresponding to each face image and the reference person based on the person name entered in the marked input.

[0211] Optionally, the processor 1110 is further configured to acquire script information related to the N script characters in the target script, wherein the script information includes at least one of the following: script title, character introduction information of the N script characters; and determine the character relationships between the N script characters based on the script information.

[0212] Optionally, the processor 1110 is further configured to classify the at least two reference images according to at least two image classification dimensions, obtaining image sets corresponding to at least two image types under each image classification dimension, wherein the image classification dimensions include at least one of time, theme, location, event, and person; for each image set corresponding to each image type under each image classification dimension, establishing object relationships between at least two objects contained in at least two reference images in each image set; wherein one image classification dimension corresponds to the generation of one object relationship graph.

[0213] Optionally, the display unit 1106 is further configured to display an object relationship map in a first screen area and display at least one image containing the target object in a second screen area; wherein the first screen area and the second screen area are areas in different displays, or the first screen area and the second screen area are different areas in the same display.

[0214] Optionally, the display unit 1106 is also used to display an object relationship graph in the target interface; and to display at least one image containing the target object in a floating window, wherein the floating window is displayed on the target interface.

[0215] Optionally, the processor 1110 is further configured to determine at least two age groups corresponding to the target object in at least two images containing the target object; and to cluster the at least two images according to the at least two age groups corresponding to the target object in the at least two images to obtain an image corresponding to each age group;

[0216] The display unit 1106 is also configured to display images corresponding to the at least two age groups in chronological order.

[0217] Optionally, the user input unit 1107 is further configured to receive a second input from the user for M object nodes in the object relationship graph, wherein M is an integer greater than 1; the M object identifiers displayed on the M object nodes indicate the M objects;

[0218] The display unit 1106 is also configured to, in response to the second input, display the group photo image if a group photo image containing the M objects exists;

[0219] The processor 1110 is further configured to, in response to the second input, output a prompt message in the absence of a group photo containing the M objects, the prompt message being used to prompt the user that a group photo containing the M objects does not exist, and to prompt the user to take a group photo containing the M objects.

[0220] It should be understood that, in this embodiment, the input unit 1104 may include a graphics processing unit (GPU) 11041 and a microphone 11042. The GPU 11041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 1106 may include a display panel 11061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 1107 includes at least one of a touch panel 11071 and other input devices 11072. The touch panel 11071 is also called a touch screen. The touch panel 11071 may include a touch detection device and a touch controller. Other input devices 11072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here.

[0221] The memory 1109 can be used to store software programs and various data. The memory 1109 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 1109 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 1109 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0222] Processor 1110 may include one or more processing units; optionally, processor 1110 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 1110.

[0223] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described image display control method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0224] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0225] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described image display control method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0226] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0227] This application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described image display control method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0228] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0229] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0230] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. An image display control method characterized by comprising: The method comprises the following steps: receiving a first input of a user on a target object node in an object relationship graph, the object relationship graph being a graph indicating object relationships of at least two objects, the object relationship graph comprising at least two object nodes, each object node displaying an object identifier, the object identifier being used to indicate an object, and a connection line being displayed between two objects having an object relationship; in the case where the number of images containing the target object is at least two, determining at least two age stages corresponding to the target object in the at least two images containing the target object in response to the first input; clustering the at least two images according to the at least two age stages corresponding to the target object in the at least two images to obtain images corresponding to each age stage; displaying the images corresponding to the at least two age stages in chronological order of the at least two age stages; the target object being an object indicated by the target object identifier displayed on the target object node.

2. The method of claim 1, wherein, Before the step of receiving the first input of the user on the target object node in the object relationship graph, the method further comprises the following steps: displaying the object relationship graph; the object comprises at least one of the following: a person, an object, an animal, and a landscape; the object relationship comprises at least one of the following: a person relationship, an ownership relationship, and an organizational relationship.

3. The method of claim 1, wherein, Before the step of receiving the first input of the user on the target object node in the object relationship graph, the method further comprises the following steps: performing object recognition on at least two reference images to obtain at least two objects; obtaining object relationships between the at least two objects; obtaining object information of the at least two objects, the object information comprising at least one of the following: an object image, an object name, and an object relationship title; generating the object relationship graph based on the object relationships between the at least two objects and the object information of the at least two objects.

4. The method of claim 3, wherein, the object comprises a person, and the object relationship comprises a person relationship; the step of obtaining the object relationships between the at least two objects comprises the following steps: cutting out at least two face images in the at least two reference images, the at least two face images being face images of different persons; receiving a marking input of a user on a target face image in the at least two cut-out face images, the marking input being used to input a person title; determining a reference person corresponding to the target face image in response to the marking input; receiving a marking input of a user on other face images, the marking input being used to input a person title; determining a person relationship between a person corresponding to each face image and the reference person based on the person title input by the marking input in response to the marking input.

5. The method of claim 3, wherein, the object comprises a person, the object relationship comprises a person relationship, and the at least two reference images are stills in a target play; the at least two reference images comprise N play characters; N is an integer greater than 1; the step of obtaining the object relationships between the at least two objects comprises the following steps: obtaining play information related to the N play characters in the target play, wherein the play information comprises at least one of the following: a play name and person introduction information of the N play characters. According to the script information, a relationship between the N script characters is determined.

6. The method of claim 3, wherein, Before the object recognition on the at least two reference images, the method further includes: According to at least two image classification dimensions, the at least two reference images are classified to obtain an image set corresponding to at least two image types in each image classification dimension, wherein the image classification dimensions include at least one of time, theme, location, event, and character; The obtaining of the object relationship between the at least two objects includes: For each image set corresponding to each image type in each image classification dimension, an object relationship between at least two objects contained in at least two reference images in each image set is established; One object relationship graph is generated for each image classification dimension.

7. The method of claim 1, wherein, Before the receiving of the first input of the user on the target object node in the object relationship graph, the method further includes: displaying the object relationship graph in a first screen area; After the receiving of the first input of the user on the target object node in the object relationship graph, the method further includes: in response to the first input, displaying at least one image containing the target object in a second screen area; The first screen area and the second screen area are areas in different display screens, or the first screen area and the second screen area are different areas in the same display screen.

8. The method of claim 1, wherein, Before the receiving of the first input of the user on the target object node in the object relationship graph, the method further includes: displaying the object relationship graph in a target interface; After the receiving of the first input of the user on the target object node in the object relationship graph, the method further includes: in response to the first input, displaying at least one image containing the target object in a floating window, wherein the floating window is displayed on the target interface.

9. The method of claim 1, wherein, The method further includes: receiving a second input of the user on M object nodes in the object relationship graph, wherein M is an integer greater than 1; M object identifiers displayed on the M object nodes indicate M objects; in response to the second input, if there is a group photo image containing the M objects, displaying the group photo image; in response to the second input, if there is no group photo image containing the M objects, outputting prompt information, the prompt information prompting that there is no group photo image containing the M objects, and prompting the user to take a group photo containing the M objects.

10. An image display control device characterized by comprising: includes: a receiving module configured to receive a first input of a user on a target object node in an object relationship graph, the object relationship graph being a graph indicating an object relationship between at least two objects, the object relationship graph including at least two object nodes, an object identifier being displayed on each object node, the object identifier being used to indicate an object, and a connection line being displayed between two objects having an object relationship; a display module configured to, in response to the first input, determine at least two age stages corresponding to the target object in at least two images containing the target object if the number of images containing the target object is at least two. According to the at least two age stages corresponding to the target object in the at least two images, the at least two images are clustered to obtain images corresponding to each age stage; According to the time sequence of the at least two age stages, the images corresponding to the at least two age stages are displayed; The target object is an object indicated by a target object identifier displayed on the target object node.

11. The apparatus of claim 10, wherein, The display module is further configured to: display an object relationship graph before receiving the first input of the user on the target object node in the object relationship graph; The object includes at least one of the following: a person, an object, an animal, and a landscape; The object relationship includes at least one of the following: a person relationship, an ownership relationship, and an organizational relationship.

12. The apparatus of claim 10, wherein, The device further includes: An identification module configured to perform object identification on at least two reference images to obtain at least two objects; An acquisition module configured to acquire an object relationship between the at least two objects and object information of the at least two objects, the object information including at least one of the following: an object image, an object name, and an object relationship title; A processing module configured to generate an object relationship graph based on the object relationship between the at least two objects and the object information of the at least two objects.

13. The apparatus of claim 12, wherein, The object includes a person, and the object relationship includes a person relationship; The processing module is further configured to extract at least two face images from the at least two reference images, the at least two face images being face images of different persons; The receiving module is further configured to receive a marking input of a target face image from the at least two extracted face images by a user, the marking input being used to input a person title; The acquisition module is further configured to determine a reference person corresponding to the target face image in response to the marking input; The receiving module is further configured to receive a marking input of other face images by a user, the marking input being used to input a person title; The acquisition module is further configured to determine a person relationship between a person corresponding to each face image and the reference person based on the person title input by the marking input in response to the marking input.

14. An electronic device, comprising: A processor and a memory, the memory stores programs or instructions executable on the processor, and the programs or instructions are executed by the processor to implement the steps of the image display control method according to any one of claims 1-9.

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