Scene linkage method and device based on playing content recognition, electronic device

Abstract

The application relates to the technical field of smart home, and discloses a scene linkage method and device based on playing content recognition and an electronic device, wherein the scene linkage method comprises the following steps: acquiring at least one frame of a picture of current playing content of a playing device; identifying the picture content to determine the type and key elements of the current playing content; and according to the identification result of the picture content, controlling smart home devices associated with the playing device to perform linkage operation based on preset scene linkage rules. The playing content recognition technology is combined with the smart home device control, the playing content picture of the playing device is analyzed in real time, the type and key elements of the playing content can be automatically identified, then based on the preset scene linkage rules, the accurate response of the smart home device can be triggered without manual operation of a user, so that the scene linkage according to the playing content is realized, and the intelligent degree of the scene linkage is improved.

Description

Technical Field

[0001] This application relates to the field of smart home technology, such as a scene linkage method and device based on playback content recognition, and electronic devices. Background Technology

[0002] Currently, with the popularization of smart homes and streaming content, users' demand for automated linkage between devices is growing. Especially in home entertainment scenarios, how to enable smart devices to dynamically adjust the environment according to the video playback content has become a technical challenge.

[0003] In related technologies, scene linkage in smart home systems requires obtaining user input commands to switch scenes and achieve scene linkage.

[0004] In the process of implementing the embodiments of this disclosure, at least the following problems were found in the related art:

[0005] In related technologies, scene-based interaction relies on user-input commands, resulting in a low level of intelligence.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0008] This disclosure provides a scene linkage method, apparatus, and electronic device based on playback content recognition to improve the intelligence level of scene linkage.

[0009] In some embodiments, the scene linkage method based on playback content recognition includes: acquiring at least one frame of the content currently being played by the playback device; recognizing the content of the frame to determine the type and key elements of the currently played content; and, based on the recognition result of the content of the frame and a preset scene linkage rule, controlling the smart home device associated with the playback device to perform linkage operations.

[0010] Optionally, the image content recognition includes: performing sentiment analysis based on the obtained image content, combined with audio features, bullet screen text, and subtitle text; and recognizing the image content based on the sentiment analysis results.

[0011] Optionally, the type of the currently played content can be determined, including: if multiple consecutive frames are identical, determining that the currently played content is a single image; or, if multiple consecutive frames are different and their contents are unrelated, determining that the currently played content is a carousel of multiple images; or, if multiple consecutive frames are different and their contents are related, determining that the currently played content is a video.

[0012] Optionally, the correlation between multiple frames can be determined by analyzing whether there are the same characters or events in the multiple frames; or by analyzing whether continuous content appears in the multiple frames.

[0013] Optionally, the scene linkage method also includes: if it is determined that the currently played content is a video, obtaining the duration of the played video; and determining the video category based on the duration of the played video.

[0014] Optionally, key elements of the currently playing content can be determined, including one or more of the following methods: extracting information about objects, people, or text in the image through image recognition technology; determining the emotional tone or scene category of the playing content by combining audio analysis; and determining the specific content or theme of the playing content by using a large model comparison database.

[0015] Optionally, the preset scene linkage rules include one or more of the following: when nervous or unsettling content is detected, control the smart lights to brighten or play soothing music; when children's educational content is detected, turn off irrelevant devices and enter focus mode; when sports events are detected, link the sound system to enhance the atmosphere and adjust the ambient lighting; when the playback time reaches the preset time, link the broadcasting device to remind the user to turn off the playback device.

[0016] Optionally, the scene linkage method also includes: establishing a personalized tag system based on the user's historical playback data; and adjusting the scene linkage rules based on the personalized tag system.

[0017] In some embodiments, the scene linkage device based on playback content recognition includes a processor and a memory storing program instructions, wherein the processor is configured to execute the scene linkage method based on playback content recognition as described above when running the program instructions.

[0018] In some embodiments, the electronic device includes: an electronic device body; and a scene linkage device based on playback content recognition, as described above, which is installed on the electronic device body.

[0019] The scene linkage method, apparatus, and electronic device based on playback content recognition provided in this disclosure can achieve the following technical effects:

[0020] In this embodiment, playback content recognition technology is combined with smart home device control. By analyzing the playback content screen of the playback device in real time, the type and key elements of the playback content can be automatically identified. Then, based on preset scene linkage rules, the smart home device can be triggered to respond accurately without manual operation by the user, thereby realizing scene linkage according to the playback content and improving the intelligence level of scene linkage.

[0021] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0022] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein:

[0023] Figure 1 This is a schematic diagram of a scene linkage method based on playback content recognition provided in an embodiment of this disclosure;

[0024] Figure 2 This is a schematic diagram of the application environment of a scene linkage method based on playback content recognition provided in an embodiment of this disclosure;

[0025] Figure 3 This is a schematic diagram of another scene linkage method based on playback content recognition provided in this embodiment of the disclosure;

[0026] Figure 4 This is a schematic diagram of a method for determining the type of currently played content, provided in an embodiment of this disclosure;

[0027] Figure 5 This is a schematic diagram of a method for adjusting scene linkage rules provided in an embodiment of this disclosure;

[0028] Figure 6 This is a schematic diagram of a scene linkage device based on playback content recognition provided in an embodiment of this disclosure. Detailed Implementation

[0029] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0030] The terms "first," "second," etc., used in the technical solutions described in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0031] Unless otherwise stated, the term "multiple" means two or more.

[0032] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0033] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0034] The term "correspondence" can refer to an association or binding relationship. The correspondence between A and B means that there is an association or binding relationship between A and B.

[0035] Combination Figure 1 As shown, this disclosure provides a scene linkage method based on playback content recognition. The execution entity of this scene linkage method can be a processor, and the scene linkage method includes:

[0036] S101, the processor acquires at least one frame of the content currently being played by the playback device.

[0037] S102, the processor identifies the content on the screen and determines the type and key elements of the content currently being played.

[0038] S103: Based on the recognition results of the screen content and the preset scene linkage rules, the processor controls the smart home devices associated with the playback device to perform linkage operations.

[0039] In this embodiment of the disclosure, combined with Figure 2 As shown, the content recognition technology of the playback device 20 is combined with the control of the smart home device 21. By analyzing the playback content of the playback device 20 in real time, the type and key elements of the playback content can be automatically identified. Then, based on the preset scene linkage rules, the smart home device 21 can be triggered to respond accurately without the user's manual operation, thereby realizing scene linkage according to the playback content and improving the intelligence level of scene linkage.

[0040] Optionally, the playback device 20 includes: smart TVs, smartphones, projectors, displays, and other devices with screens.

[0041] Optionally, smart home device 21 includes: smart lighting devices, multimedia devices, audio devices, and motorized curtains.

[0042] Optionally, acquiring at least one frame of the content currently being played by the playback device includes: acquiring frame images multiple times at preset time intervals by capturing images.

[0043] Optionally, the image content recognition includes: performing sentiment analysis based on the obtained image content, combined with audio features, bullet screen text, and subtitle text; and recognizing the image content based on the sentiment analysis results.

[0044] Combination Figure 3 As shown, this disclosure provides another scene linkage method based on playback content recognition, including:

[0045] S301, the processor acquires at least one frame of the content currently being played by the playback device.

[0046] S302, the processor performs sentiment analysis based on the obtained video content, combined with audio features, bullet screen text, and subtitle text.

[0047] S303: The processor identifies the content of the screen based on the sentiment analysis results, and determines the type and key elements of the content currently being played.

[0048] S304: Based on the recognition results of the screen content and according to preset scene linkage rules, the processor controls the smart home devices associated with the playback device to perform linkage operations.

[0049] In this embodiment, after preprocessing the acquired video content such as noise reduction, super-resolution enhancement, and key region detection, multimodal feature extraction can be performed. For example, features such as objects, scenes, and facial expressions in the video are extracted; text content in the video is identified; acoustic features such as MFCC (Mel-Frequency Cepstral Coefficients), pitch, and rhythm are extracted; speech recognition is performed based on audio features, and sentiment analysis is combined with natural language processing; and text sentiment is extracted from bullet screen text and subtitle text. Then, sentiment analysis is performed based on visual, audio, and text features to output a comprehensive sentiment label and content type. Combining sentiment analysis with content recognition allows for high-precision identification of video content, and multimodal complementarity solves the ambiguity of single modalities, such as a "funny / scare movie" with dark visuals but cheerful background music.

[0050] Optionally, the type of the currently played content can be determined, including: if multiple consecutive frames are identical, determining that the currently played content is a single image; or, if multiple consecutive frames are different and their contents are unrelated, determining that the currently played content is a carousel of multiple images; or, if multiple consecutive frames are different and their contents are related, determining that the currently played content is a video.

[0051] Combination Figure 4 As shown, this disclosure provides a method for determining the type of currently playing content. The execution entity of this method may be a processor, and the method includes:

[0052] S401, the processor determines whether multiple consecutive frames are identical. If yes, it executes S402; otherwise, it executes S403.

[0053] S402, the processor determines that the currently playing content is a single image.

[0054] S403, the processor determines whether the content of multiple consecutive frames is related. If so, it executes S405; otherwise, it executes S404.

[0055] S404, the processor determines that the currently playing content is a carousel of multiple images.

[0056] S405, the processor determines that the currently playing content is a video.

[0057] In this embodiment, high-precision content type identification can be achieved through multi-frame difference analysis and content correlation verification. By comparing pixels or matching features across multiple consecutive frames, images that are completely identical are identified as static images, avoiding misclassification of paused videos as images. Through image difference analysis and semantic coherence detection, scenarios such as electronic photo albums and advertising carousels can be identified even when multiple frames have different content but no temporal correlation, reducing the probability of misclassification as video. Therefore, by using the structural similarity of consecutive frames and detecting spatiotemporal continuity based on optical flow or 3D convolutional neural networks, videos and fast-moving carousels can be effectively distinguished.

[0058] Optionally, the correlation between multiple frames can be determined by analyzing whether there are the same characters or events in the multiple frames; or by analyzing whether continuous content appears in the multiple frames.

[0059] In this embodiment, object detection is used to track the same person or object across multiple frames, and behavior recognition is combined to determine event continuity. This accurately distinguishes between videos and carousels, avoiding misidentification of rapidly switching close-ups of people as carousels. By analyzing the semantic coherence of subtitles or audio, and using optical flow or temporal modeling to detect the dynamic continuity of images, it is possible to identify educational videos and advertising carousels, and differentiate complex scenes, such as distinguishing between PPT presentations and animated short films. Therefore, through the detection of the continuity of people or events, and the analysis of content logical relationships, reliable differentiation between videos, carousels, and still images can be achieved.

[0060] Optionally, the scene linkage method also includes: if it is determined that the currently played content is a video, obtaining the duration of the played video; and determining the video category based on the duration of the played video.

[0061] In this embodiment, after identifying the playback content as video, further refined classification is achieved through video duration analysis, such as short videos, movies, and TV series. The total duration can be obtained from video metadata or the player interface. Based on preset rules, for example: if the total duration is less than 2 minutes, it is determined to be a short video; if the total duration is greater than 5 minutes but less than 10 minutes, it is determined to be a medium-length video; if the total duration is greater than 30 minutes but less than 50 minutes, it is determined to be a TV series; and if the total duration is greater than 90 minutes, it is determined to be a movie. In addition, if the total duration is within the threshold boundary, intro and outro detection, as well as chapter marking, can be performed for supplementary analysis. For example, if a black screen and subtitles appear in the intro or outro, it is determined to be a TV series; if chapter markings such as MKV (Matroska Video) segments appear, it is determined to be a movie. Therefore, by using video duration as a key metadata, the shortcomings of pure visual analysis in video type identification can be compensated for.

[0062] Optionally, key elements of the currently playing content can be determined, including one or more of the following methods: extracting information about objects, people, or text in the image through image recognition technology; determining the emotional tone or scene category of the playing content by combining audio analysis; and determining the specific content or theme of the playing content by using a large model comparison database.

[0063] In this embodiment, key elements of the playback content are accurately extracted by combining image recognition, audio analysis, and large-scale model comparison. This overcomes the limitations of a single sensor and adapts to complex playback environments. Furthermore, through deep semantic understanding, it enables an upgrade from "object recognition" to "emotion and theme inference."

[0064] Optionally, image recognition technology can be used to extract information about objects, people, or text in the image, including: identifying objects and people in the image through target detection, such as cars, tableware, main characters, and celebrities; extracting text information such as subtitles, poster text, and interface buttons through optical character recognition technology; and determining the content scene through scene classification, such as indoor, outdoor, and night scenes.

[0065] Optionally, audio analysis can be combined to determine the emotional tone or scene category of the played content, including: determining the background music type through acoustic feature extraction, such as exciting or soothing; identifying the emotions of the dialogue through voice emotion analysis, such as anger or joy; and assisting in scene classification through environmental sound detection, such as concerts or war movies.

[0066] Optionally, through multimodal retrieval, the visual or audio features are compared with the film and television database to match specific content, such as "The Avengers"; through knowledge graph association, the theme is inferred by combining characters, objects, and text, such as inferring that the subject is "science fiction" by using "Iron Man + suit".

[0067] Optionally, the preset scene linkage rules include one or more of the following: when nervous or unsettling content is detected, control the smart lights to brighten or play soothing music; when children's educational content is detected, turn off irrelevant devices and enter focus mode; when sports events are detected, link the sound system to enhance the atmosphere and adjust the ambient lighting; when the playback time reaches the preset time, link the broadcasting device to remind the user to turn off the playback device.

[0068] In this embodiment, by using preset scene linkage rules, the results of image content recognition are converted into specific device control commands, enabling highly personalized and automated environmental adaptation. Specifically, real-time emotion analysis detects elements of tension or anxiety, such as dark scenes or screaming sound effects, triggering brighter lights and the playback of soothing music. This enhances the user's sense of security and prevents viewing interruptions due to unpleasant content. Upon recognizing educational content, such as "mathematics" or "ABC" in animated subtitles, the entertainment functions of unrelated devices like smart speakers are turned off, and unrelated lights are dimmed, leaving only the reading light on. This increases focus time and reduces interference from multiple devices. When a team logo is recognized and cheers are detected, "Field Mode" is activated, dynamically enhancing the commentary frequency and synchronizing the lights with the home team's color, thus improving viewer immersion. When the cumulative playback time reaches a threshold, a notification is given, such as, "You have watched continuously for 120 minutes; a break is recommended," increasing the rate of users voluntarily pausing the viewing.

[0069] Optionally, the scene linkage method also includes: establishing a personalized tag system based on the user's historical playback data; and adjusting the scene linkage rules based on the personalized tag system.

[0070] Combination Figure 5 As shown, this disclosure provides a method for adjusting scene linkage rules. The execution subject of this method can be a processor, and the method includes:

[0071] The S501 processor establishes a personalized tagging system based on the user's historical playback data.

[0072] The S502 processor adjusts scene linkage rules based on a personalized tagging system.

[0073] In this embodiment, a personalized tagging system is constructed by analyzing users' historical playback behavior, and the linkage rules are dynamically adjusted, achieving an upgrade from generalized linkage to intelligent adaptation. Collaborative filtering algorithms are used to analyze viewing records, and user-manually set tags, such as "dislikes comedies," are parsed through a model to obtain a personalized tagging system, accurately predicting user preferences. Then, based on user preferences, a rule engine based on reinforcement learning automatically selects the optimal linkage strategy and adjusts the scene linkage rules, thereby improving user satisfaction and increasing user willingness to use the device. For example, in a movie playback scene, the default scene linkage rule is to uniformly dim the lights. Based on the user's personalized tags, if the user prefers science fiction, blue ambient light can be selected; if the user prefers art films, suitable warm light can be selected. For children's content, the default scene linkage rule is a fixed-duration reminder. Based on the user's personalized tags, if the child is 3 years old, a reminder is set every 15 minutes; if the child is 10 years old, a reminder is set every 30 minutes. If it is detected that the user typically watches news between 7:00 and 7:30, the lights are automatically brightened and the curtains are closed to reduce glare during the corresponding time. If the history shows that users support the same team when watching sports events, the TV will automatically turn on and the team-colored lights will be enabled when the game starts.

[0074] Combination Figure 6 As shown, this disclosure provides a scene linkage device 600 based on playback content recognition, including a processor 601 and a memory 602. Optionally, the device may further include a communication interface 603 and a bus 604. The processor 601, communication interface 603, and memory 602 can communicate with each other via the bus 604. The communication interface 603 can be used for information transmission. The processor 601 can call logical instructions in the memory 602 to execute the scene linkage method based on playback content recognition described in the above embodiment.

[0075] Furthermore, the logic instructions in the aforementioned memory 602 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0076] The memory 602, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 601 executes functional applications and data processing by running the program instructions / modules stored in the memory 602, thereby realizing the scene linkage method based on playback content recognition in the above embodiments.

[0077] The memory 602 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 602 may include high-speed random access memory and may also include non-volatile memory.

[0078] This disclosure provides an electronic device, including: an electronic device body, and the aforementioned scene linkage device based on playback content recognition. The scene linkage device based on playback content recognition is installed on the electronic device body. The installation relationship described herein is not limited to placement inside the electronic device, but also includes installation and connection with other components of the electronic device, including but not limited to physical connections, electrical connections, or signal transmission connections. Those skilled in the art will understand that the scene linkage device based on playback content recognition can be adapted to feasible electronic device bodies, thereby realizing other feasible embodiments.

[0079] This disclosure provides a computer-readable storage medium storing computer-executable instructions configured to execute the above-described scene linkage method based on playback content recognition.

[0080] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, including: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code.

[0081] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the technical solutions described herein. As used in the technical solutions described herein, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used herein means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0082] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0083] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0084] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A scene linkage method based on playback content recognition, characterized in that, include: Get at least one frame of the content currently being played on the playback device; Identify the content on the screen to determine the type and key elements of the currently playing content; Based on the recognition results of the screen content and the preset scene linkage rules, the smart home devices associated with the playback device are controlled to perform linkage operations.

2. The scene linkage method according to claim 1, characterized in that, Content recognition of the image, including: Based on the obtained video content, combined with audio features, bullet screen text, and subtitle text, sentiment analysis is performed; Based on the sentiment analysis results, the content of the image is identified.

3. The scene linkage method according to claim 1, characterized in that, Determine the type of content currently being played, including: If multiple consecutive frames are identical, determine that the currently playing content is a single image; or, If multiple consecutive frames are different and their content is unrelated, determine that the currently playing content is a slideshow of multiple images; or, If multiple consecutive frames are different but their content is related, the currently playing content is determined to be video.

4. The scene linkage method according to claim 3, characterized in that, The correlation between multiple frames is determined as follows: Analyze whether the same people or events exist in multiple frames; or, Analyze whether continuous content appears in multiple frames.

5. The scene linkage method according to claim 3, characterized in that, Also includes: If it is determined that the currently playing content is a video, obtain the duration of the video being played; The video category is determined based on its duration.

6. The scene linkage method according to claim 1, characterized in that, Identify key elements of the currently playing content, including one or more of the following methods: Extracting information about objects, people, or text from images using image recognition technology; By combining audio analysis, we can determine the emotional tone or scene category of the content being played. By using a large model to compare with a database, the specific content or theme of the content to be played can be determined.

7. The scene linkage method according to any one of claims 1 to 6, characterized in that, The preset scene linkage rules include one or more of the following: When it detects stressful or unsettling content, it controls the smart lights to brighten or plays soothing music. Upon detecting educational content for children, irrelevant devices are turned off and a focus mode is entered. When a sporting event is detected, the system will activate the sound system to enhance the atmosphere and adjust the ambient lighting. When the playback duration reaches the preset time, the linked broadcast device will remind the user to turn off the playback device.

8. The scene linkage method according to claim 7, characterized in that, Also includes: Establish a personalized tagging system based on users' historical playback data; Adjust the scene linkage rules based on the personalized tagging system.

9. A scene linkage device based on playback content recognition, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to execute the scene linkage method based on playback content recognition as described in any one of claims 1 to 8 when running the program instructions.

10. An electronic device, characterized in that, include: The electronic device itself; The scene linkage device based on playback content recognition as described in claim 9 is installed on the electronic device body.

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