Video recording method, vehicle and storage medium

Abstract

The invention provides a video recording method, a vehicle and a storage medium, and the method is applied to the field of vehicles, and the method comprises the steps: recognizing the current driving road condition of a target vehicle when the current coordinate information of the target vehicle is matched with the historical high-heat recording scene coordinate information in a video recording database, and when the current driving road condition of the target vehicle meets the video recording condition, generating video recording prompt information, and under the condition that a confirmation instruction sent by a user based on the video recording prompt information is received, executing a video recording action. According to the method, a hot video recording database is constructed, the database is combined with a real-time vehicle state, and when a user is about to arrive at a high-value scene, the user is actively prompted and assisted to carry out video recording with optimal parameter setting, so that intelligent, scene-based and high-social-value video automatic acquisition is finally realized.

Description

Technical Field

[0001] This application relates to the field of vehicles, and more specifically, to video recording methods, vehicles, and storage media in the field of vehicles. Background Technology

[0002] With the increasing popularity of smart cars and short video social platforms, more and more users want to record wonderful moments during their journeys and share their lives through video recordings.

[0003] In related technologies, functions such as intelligent photography and intelligent video recording are mainly triggered by the user manually, or automatically recorded at a set fixed time or distance interval, or automatically started recording when the camera captures a preset scene (such as a specific landmark or landscape) based on image recognition technology.

[0004] However, the above recording methods have certain drawbacks: (1) Manual recording poses safety hazards during driving and may cause you to miss exciting moments; (2) Timed and distanced recording may generate a large number of invalid videos, thereby increasing the cost of later storage and screening; (3) Image recognition schemes are limited by factors such as weather, lighting, and occlusion, resulting in low recognition accuracy and a lack of intelligent recognition capabilities for "high-value scenes", which urgently needs to be addressed. Summary of the Invention

[0005] This application provides a video recording method, a vehicle, and a storage medium. The method constructs a popular video recording database and uses this database in conjunction with real-time vehicle status to proactively prompt and assist users in setting optimal parameters for video recording when they are about to arrive at a high-value scene, thereby ultimately achieving intelligent, contextualized, and high-social-value automatic video acquisition.

[0006] Firstly, a video recording method is provided, comprising: acquiring the current coordinate information of a target vehicle; if the current coordinate information matches the coordinate information of historically popular recording scenes in a pre-built video recording database, identifying the current driving conditions of the target vehicle and determining whether the current driving conditions of the target vehicle meet the video recording conditions, wherein the video recording database is dynamically constructed based on historical video recording information of other vehicle users and video feedback information from preset social platforms; if the current driving conditions of the target vehicle meet the video recording conditions, generating video recording prompt information, and executing a video recording action upon receiving a confirmation instruction from a user based on the video recording prompt information.

[0007] Through the above technical solution, by constructing a video recording database based on "historical recording information of other vehicles" and "user feedback data from social platforms" (likes, views, and favorites), the system quantifies the real preferences of a massive number of users into a comprehensive popularity score. At the same time, combined with the real-time vehicle status, when the user is about to arrive at a high-value scene, it will proactively prompt and assist them in recording video with optimal parameter settings, thereby ultimately realizing intelligent, scenario-based, and high social value automatic video acquisition.

[0008] In conjunction with the first aspect, in some possible implementations, before obtaining the current coordinate information of the target vehicle, the method further includes: obtaining historical video recording information of other vehicle users and / or video feedback information from the preset social platform; identifying the first location coordinates of the historical video recording information and / or the second location coordinates of the video feedback information based on a preset interface; obtaining the coordinate information of the historical high-popularity recording scene based on the first location coordinates and / or the second location coordinates; and constructing the video recording database based on the coordinate information of the historical high-popularity recording scene.

[0009] By analyzing a large amount of real user feedback data (likes, views, favorites) on social platforms, the above technical solution constructs a high-popularity recording scene information recommended by a large number of users. This ensures that the recommended recording scene information is a high-value scene verified by a large number of users, greatly enhancing the attractiveness and social potential of the recorded content.

[0010] Combining the first aspect and the above implementation methods, in some possible implementation methods, determining whether the current coordinate information matches the coordinate information of historically popular recorded scenes in a pre-built video recording database includes: matching the corresponding target video from the video recording database based on the current coordinate information of the target vehicle; calculating the comprehensive popularity score of the target video; determining whether the comprehensive popularity score is greater than a first preset score threshold; if the comprehensive popularity score is greater than the first preset score threshold, then determining that the current coordinate information matches the coordinate information of historically popular recorded scenes in the video recording database; if the comprehensive popularity score is less than or equal to the first preset score threshold, then determining that the current coordinate information does not match the coordinate information of historically popular recorded scenes in the video recording database.

[0011] By using the above technical solutions, the system can make a comprehensive and scientific evaluation based on real data (views, likes, favorites) by calculating the comprehensive popularity score of the target video corresponding to the current coordinate information. This makes the system's recommendations no longer random or based on simple rules, but evidence-based, repeatable, and verifiable, greatly improving the credibility and accuracy of the decision-making.

[0012] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the calculation of the comprehensive popularity score of the target video includes: obtaining the current number of views, current number of likes, and current number of favorites of the target video; calculating the first product of the current number of views and a first weight coefficient, the second product of the current number of likes and a second weight coefficient, and the third product of the current number of favorites and a third weight coefficient; and obtaining the comprehensive popularity score of the target video based on the first product, the second product, and the third product.

[0013] By using the above technical solutions, the system can make a comprehensive and scientific evaluation based on real data (views, likes, favorites) by calculating the comprehensive popularity score of the target video corresponding to the current coordinate information. This makes the system's recommendations no longer random or based on simple rules, but evidence-based, repeatable, and verifiable, greatly improving the credibility and accuracy of the decision-making.

[0014] In combination with the first aspect and the above implementation methods, in some possible implementation methods, determining whether the current driving conditions of the target vehicle meet the video recording conditions includes: determining whether the vehicle speed information of the target vehicle is within a preset speed range, and determining whether the camera of the target vehicle is in an unobstructed state; if the vehicle speed information is within the preset speed range and the camera is in the unobstructed state, then it is determined that the current driving conditions of the target vehicle meet the video recording conditions.

[0015] By using the above technical solution, the active prompts for video scene recording are based on safe driving by identifying the current driving conditions of the target vehicle. This can fundamentally prevent the system from interfering with driving due to recommended recording. At the same time, it can also avoid generating low-quality videos that are blurry, shaky, obscured, or poorly composed, thus ensuring the viewing quality of the final video recording.

[0016] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the video recording action includes: recording the road scene in front of the target vehicle and the road scene on both sides based on the first camera, recording the road scene behind the target vehicle based on the second camera, and recording the user status information inside the target vehicle based on the third camera; combining the road scene in front of the target vehicle and the road scene on both sides, the road scene behind the target vehicle, and the user status information inside the target vehicle into a video recording database to obtain the final video recording information; and saving the video parameters of the final video recording information to the video recording database.

[0017] The above technical solution allows the vehicle's camera to begin recording after receiving a confirmation command from the user based on the video recording prompt. This achieves the best balance between intelligent recommendations and user-initiated decision-making, ensuring driving safety and respecting user wishes. It also avoids privacy leaks and user complaints that may result from fully automatic recording.

[0018] In combination with the first aspect and the above implementation methods, in some possible implementation methods, after obtaining the final video recording information and saving the video parameters of the final video recording information to the video recording database, the method further includes: obtaining the latest number of views, the latest number of likes, and the latest number of favorites of the final video recording information based on a preset interface; and updating the new coordinate information corresponding to the final video recording information and the comprehensive popularity score of the video parameters in the video recording database based on the latest number of views, the latest number of likes, and the latest number of favorites of the final video recording information.

[0019] Through the above technical solution, by updating the video recording database in real time, the system can quickly capture changes in hot scenes and include them in high-popularity recommendations. Conversely, if a scenic spot's popularity drops sharply due to closure or negative news, the system can also promptly lower its recommendation weight, thereby ensuring the freshness and relevance of the recommendation results.

[0020] Secondly, a video recording apparatus is provided, the apparatus comprising: The acquisition module is used to obtain the current coordinate information of the target vehicle; The identification module is used to identify the current driving conditions of the target vehicle if the current coordinate information matches the coordinate information of historical high-popularity recording scenes in the pre-built video recording database, and to determine whether the current driving conditions of the target vehicle meet the video recording conditions. The video recording database is dynamically constructed based on the historical video recording information of other vehicle users and the video feedback information of preset social platforms. The video recording module is used to generate a video recording prompt message if the current driving conditions of the target vehicle meet the video recording conditions, and to execute the video recording action upon receiving a confirmation command from the user based on the video recording prompt message.

[0021] In conjunction with the second aspect, in some possible implementations, before obtaining the current coordinate information of the target vehicle, the acquisition module further includes: The acquisition unit is used to acquire historical video recording information of the other vehicle users and / or video feedback information from the preset social media platform; The identification unit is used to identify the first position coordinates of the historical video recording information and / or the second position coordinates of the video feedback information based on a preset interface; The construction unit is used to obtain the coordinate information of the historical high-popularity recording scene based on the first position coordinates and / or the second position coordinates, and to construct the video recording database based on the coordinate information of the historical high-popularity recording scene.

[0022] In combination with the second aspect and the above implementation methods, in some possible implementations, the identification module includes: A matching unit is used to match the corresponding target video from the video recording database based on the current coordinate information of the target vehicle; A calculation unit is used to calculate the overall popularity score of the target video; The first determination unit is used to determine whether the overall popularity score is greater than a first preset score threshold. If the overall popularity score is greater than the first preset score threshold, it is determined that the current coordinate information matches the coordinate information of historical high-popularity recording scenes in the video recording database. If the overall popularity score is less than or equal to the first preset score threshold, it is determined that the current coordinate information does not match the coordinate information of historical high-popularity recording scenes in the video recording database.

[0023] In combination with the second aspect and the above implementation methods, in some possible implementations, the computing unit includes: The first acquisition subunit is used to acquire the current number of views, current number of likes, and current number of favorites of the target video; The calculation subunit is used to calculate the first product of the current number of views and the first weight coefficient, the second product of the current number of likes and the second weight coefficient, and the third product of the current number of favorites and the third weight coefficient. The second acquisition subunit is used to obtain the comprehensive popularity score of the target video based on the first product, the second product and the third product.

[0024] In combination with the second aspect and the above implementation methods, in some possible implementations, the identification module includes: The judgment unit is used to determine whether the speed information of the target vehicle is within a preset speed range, and to determine whether the camera of the target vehicle is in an unobstructed state. The second determination unit is used to determine that the current driving conditions of the target vehicle meet the video recording conditions if the vehicle speed information is within the preset vehicle speed range and the camera is in the unobstructed state.

[0025] In combination with the second aspect and the above implementation methods, in some possible implementations, the video recording module includes: The video recording unit is used to record the road scene in front of the target vehicle and the road scene on both sides based on the first camera, and to record the road scene behind the target vehicle based on the second camera, and to record the user status information inside the target vehicle based on the third camera. The video synthesis unit is used to synthesize the road scenes in front of the target vehicle and the roads on both sides, the road scene behind the target vehicle, and the user status information inside the target vehicle to obtain the final video recording information and save the video parameters of the final video recording information to the video recording database.

[0026] In conjunction with the second aspect and the above implementation methods, in some possible implementation methods, after obtaining the final video recording information and saving the video parameters of the final video recording information to the video recording database, the video synthesis unit further includes: The third acquisition subunit is used to acquire the latest number of views, the latest number of likes, and the latest number of favorites of the final video recording information based on a preset interface. The update subunit is used to update the new coordinate information and video parameters corresponding to the final video recording information in the video recording database based on the latest number of views, likes, and favorites of the final video recording information.

[0027] Thirdly, a vehicle is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the video recording method as described in any one of claims 1-7.

[0028] Fourthly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0029] Fifthly, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof. Attached Figure Description

[0030] Figure 1 A flowchart illustrating the video recording method provided in this application embodiment; Figure 2 A block diagram of the video recording device provided in the embodiments of this application; Figure 3 This is a schematic diagram of the vehicle structure according to an embodiment of this application. Detailed Implementation

[0031] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0032] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0033] With the rapid development of intelligent connected vehicle technology and the popularization of short video social platforms on the Internet, more and more users want to record the scenery or interesting things along the way during their driving journey and share their lives in the form of Vlogs, which has given rise to the demand for in-vehicle scene-based video recording functions. However, existing in-vehicle recording technologies still have significant shortcomings in terms of intelligence, safety and user experience. For example, the relevant technologies mainly record videos in the following ways: (1) Manually triggered recording: The user manually starts the recording function through voice commands or buttons on the vehicle screen; (2) Automatic recording at fixed time and distance: The system automatically starts recording according to the preset time interval (such as every 5 minutes) or driving distance (such as every 1 kilometer); (3) Scene-triggered recording based on image recognition: The in-vehicle camera is used to capture the scene outside the vehicle, and the computer vision algorithm is used to compare it with the preset image library. When a specific object (such as a landmark building, mountains and rivers) is identified, the recording is automatically started. However, the above recording methods have certain defects: (1) Manual recording poses safety hazards during driving and is easy to miss wonderful moments; (2) Timed and distance recording may generate a large number of invalid videos, thereby increasing the storage and screening costs in the later stage and resulting in a poor user experience; (3) Image recognition schemes are limited by factors such as weather, lighting, and occlusion, resulting in low recognition accuracy and lack of intelligent recognition capabilities for "high-value scenes".

[0034] Therefore, based on the aforementioned problems, this application embodiment constructs a cloud database of "popular recording points" driven by user-contributed data. By combining this database with real-time vehicle status (GPS (Global Positioning System), vehicle speed, lane, road conditions, etc.), it proactively prompts and assists users in setting optimal parameters for video recording when they are about to drive to a high-value scene, thereby ultimately achieving intelligent, contextualized, and high-social-value automatic video acquisition.

[0035] Figure 1 This is a schematic flowchart of a video recording method provided in an embodiment of this application.

[0036] For example, such as Figure 1 As shown, the method includes: In step S101, the current coordinate information of the target vehicle is obtained.

[0037] Optionally, in one embodiment of this application, before obtaining the current coordinate information of the target vehicle, the method further includes: obtaining historical video recording information of other vehicle users and / or video feedback information from preset social platforms; identifying the first location coordinates of the historical video recording information and / or the second location coordinates of the video feedback information based on a preset interface; obtaining the coordinate information of historically popular recording scenes based on the first location coordinates and / or the second location coordinates; and constructing a video recording database based on the coordinate information of historically popular recording scenes.

[0038] The preset interfaces can be selected by those skilled in the art based on actual video recording needs, and the preset social platforms can be relevant social platforms that users frequently browse or that are recommended based on user preferences; no specific limitations are made here.

[0039] Specifically, to address the issue that users may miss beautiful scenery or popular photo spots while driving due to safety concerns, or they may be unable to determine which scenic spots are high-value photo spots based solely on their own judgment, or even if they successfully record, the video quality may be low due to excessive speed or improper lane selection, failing to meet the user's recording needs, this application aims to enable the video recording function to be activated in advance and provide feedback when the user is about to reach a popular photo spot, thereby achieving the purpose of recording life and sharing fun. This can be divided into two stages: the data accumulation and database construction stage and the intelligent service and proactive prompt stage.

[0040] Specifically, in the data accumulation and database construction phase, data collection is required first. When a user installs and launches the in-vehicle video application, the system requests and obtains the user's authorization. At this time, the user logs into the in-vehicle video application to authenticate their identity and authorize the system. After authorization, the user information can be uploaded to the cloud. At the same time, user information of other vehicles around the current vehicle can also be obtained. For example, historical video recording information of other vehicle users when driving to historically popular recording scenes and / or video feedback information from preset social media platforms can be obtained. In other words, the user information of the current vehicle can be shared with the user information of other vehicles through the cloud. When the user turns on the video recording function, when the user drives to a historically popular recording scene, the system will automatically collect and record the vehicle's coordinate information, status information, and environmental information of the vehicle, such as the lane the vehicle is in, the name of the road segment, the vehicle's speed, and the road conditions. If the user has not authorized the system, authorization will be prompted during subsequent video recording.

[0041] Secondly, users can record and edit videos based on the information collected above according to their own preferences, and can share them to preset social platforms. At this time, the system identifies the first location coordinates of historical video recording information and / or the second location coordinates of video feedback information through preset interfaces, such as API (Application Programming Interface). In other words, the system captures the geolocation tags of the corresponding videos based on historically uploaded video recording information and / or video feedback information from preset social platforms, namely the first location coordinates of historical video recording information and the second location coordinates of video feedback information. The first and second location coordinates are the coordinate information corresponding to historically popular recording scenes. Therefore, the embodiments of this application can construct a video recording database based on the coordinate information of historically popular recording scenes.

[0042] Among them, historically popular recording scenes refer to locations or road segments where multiple vehicle users have actively recorded videos in the vicinity of the geographical location within a certain period of time, and these videos have received high user interaction feedback (such as likes, views, and collections) after being uploaded to preset social platforms (such as video apps). The coordinate information of historically popular recording scenes refers to one or more sets of latitude and longitude data (i.e., GPS (Global Positioning System) coordinates) used to accurately identify the geographical location of the "historically popular recording scene", and usually also includes recommended recording parameters (such as recommended speed and recommended lane) associated with the coordinate information.

[0043] For example, if a certain night view section, art check-in point, scenic spot check-in point, etc. have been actively recorded by multiple vehicle users, and the recorded videos have received high attention and feedback after being uploaded to the video APP, then the night view section, art check-in point, scenic spot check-in point in a certain place can be used as historical high-heat recording scenes, and the corresponding historical high-heat recording scene coordinate information can be identified, so as to activate the video recording function when the user of the current vehicle is about to drive to the above-mentioned locations.

[0044] Thus, by analyzing the real feedback data (likes, views, collections) of a large number of users on the social platform, a high-heat recording scene information recommended by the majority of users is constructed, so as to ensure that the recommended recording scene information is a high-value scene verified by a large number of users, greatly enhancing the attractiveness and social potential of the recorded content.

[0045] Optionally, in an embodiment of the present application, determining whether the current coordinate information matches the historical high-heat recording scene coordinate information in the pre-constructed video recording database includes: based on the current coordinate information of the target vehicle, matching the corresponding target video from the video recording database; calculating the comprehensive heat score of the target video; determining whether the comprehensive heat score is greater than the first preset score threshold. If the comprehensive heat score is greater than the first preset score threshold, it is determined that the current coordinate information matches the historical high-heat recording scene coordinate information in the video recording database. If the comprehensive heat score is less than or equal to the first preset score threshold, it is determined that the current coordinate information does not match the historical high-heat recording scene coordinate information in the video recording database.

[0046] Optionally, in an embodiment of the present application, calculating the comprehensive heat score of the target video includes: obtaining the current view count, current like count, and current collection count of the target video; calculating the first product of the current view count and the first weight coefficient, the second product of the current like count and the second weight coefficient, and the third product of the current collection count and the third weight coefficient; obtaining the comprehensive heat score of the target video according to the first product, the second product, and the third product.

[0047] Among them, the first preset score threshold can be set by those skilled in the art according to actual video recording requirements, or obtained through comprehensive determination based on the historical video recording information feedback by other vehicle users and / or the video feedback information of the preset social platform, and no specific limitation is made here.

[0048] Specifically, during vehicle operation, the on-board terminal acquires the current coordinate information of the target vehicle at a fixed frequency or a target frequency set by the user according to the video recording requirements, such as acquiring the current coordinate information of the target vehicle once every 6 seconds to 10 minutes. Then, the current coordinate information of the target vehicle is uploaded to the cloud, and based on the current coordinate information of the target vehicle, it is matched with the coordinate information corresponding to all historical high-popularity recording scenes stored in the video recording database constructed above to determine whether the vehicle is about to enter or approach a high-popularity recording scene.

[0049] Specifically, firstly, the overall popularity score of the target video corresponding to the current coordinate information is calculated. This mainly includes: obtaining the current number of views, likes, and favorites of the target video, and calculating the first product of the current number of views and the first weight coefficient, the second product of the current number of likes and the second weight coefficient, and the third product of the current number of favorites and the third weight coefficient. For example, the first weight coefficient can be 50%, the second weight coefficient can be 30%, and the third weight coefficient can be 20%. Then, the overall popularity score corresponding to the current coordinate information is obtained by summing the first, second, and third products. The specific expression is as follows: (Current pageviews / User-preset pageviews) * 50% + (Current likes / User-preset likes) * 30% + (Current favorites / User-preset favorites) * 20% ≥ 1; Furthermore, based on the above calculations, if the overall popularity score is greater than the first preset score threshold (i.e., 1), it is determined that the current coordinate information matches the coordinate information of historical high-popularity recording scenes in the video recording database. In other words, the vehicle is about to enter or approach a high-popularity recording scene. If the overall popularity score is less than or equal to the first preset score threshold, it is determined that the current coordinate information does not match the coordinate information of historical high-popularity recording scenes in the video recording database, and video recording will not be performed.

[0050] Therefore, by calculating the comprehensive popularity score of the target video corresponding to the current coordinate information, the system can conduct a comprehensive and scientific evaluation based on real data (views, likes, collections), making the system's recommendations no longer random or based on simple rules, but evidence-based, repeatable, and verifiable, greatly improving the credibility and accuracy of decision-making.

[0051] In step S102, if the current coordinate information matches the coordinate information of historically popular recording scenes in the pre-built video recording database, the current driving conditions of the target vehicle are identified, and it is determined whether the current driving conditions of the target vehicle meet the video recording conditions. The video recording database is dynamically constructed based on the historical video recording information of other vehicle users and the video feedback information of preset social platforms.

[0052] Specifically, during the intelligent service and proactive prompting phase, if the current coordinate information matches the coordinate information of historically popular recording scenes in the pre-built video recording data, it indicates that the user is about to enter a historically popular recording scene. The system needs to immediately initiate real-time perception of the target vehicle's current operating status, i.e., identify the current driving conditions. The current driving conditions mainly refer to vehicle parameters and sensor states that directly affect the safety and image quality of video recording. Based on the identification results, the system determines whether the current driving conditions meet the video recording conditions. These video recording conditions refer to a set of pre-set rules to ensure driving safety and video content quality. Only when all indicators in the "current driving conditions" meet these conditions will the system consider the video recording conditions to be met, in order to avoid situations such as scene obstruction or unclear video recording due to excessive vehicle speed.

[0053] Optionally, in one embodiment of this application, determining whether the current driving conditions of the target vehicle meet the video recording conditions includes: determining whether the vehicle speed information of the target vehicle is within a preset speed range, and determining whether the camera of the target vehicle is in an unobstructed state; if the vehicle speed information is within the preset speed range and the camera is in an unobstructed state, then it is determined that the current driving conditions of the target vehicle meet the video recording conditions.

[0054] The preset speed range can be set to ensure the stability of video recording.

[0055] Specifically, after determining that the current coordinate information matches the coordinate information of historically high-traffic recording scenes in the pre-built video recording data, the first step is to identify the current driving conditions of the target vehicle and upload the identified current driving conditions to the cloud for data merging. For example, the current driving conditions may include the target vehicle's speed information, the lane the target vehicle is in, and the name of the road segment. Among these, the speed information can determine whether the target vehicle's current speed is within a preset speed range, i.e., whether the current speed is too fast. The lane the target vehicle is in can determine whether the target vehicle is driving stably. The presence of lane centering and frequent lane changes or line crossings, along with the road segment name, can indicate whether there are no-parking or temporary parking restrictions. If the speed is too high (e.g., >100km / h), even with a clear image, fast-moving objects will result in an unpleasant viewing experience. Next, it's determined whether the target vehicle's camera is unobstructed. That is, after acquiring the vehicle's current road conditions, the vehicle's camera can scan the target vehicle to further assess the road conditions. If the target vehicle is in good road conditions, its speed is within the recommended video recording speed range (e.g., 20 km / h - 80 km / h), the camera is clearly visible and unobstructed, and the vehicle is driving steadily, then the current road conditions meet the video recording requirements and are suitable for recording. However, if the current road conditions are complex, such as congested roads ahead, sudden accidents, or inclement weather, recording will severely impact video quality. Therefore, the current road conditions do not meet the video recording requirements and are unsuitable for recording.

[0056] Therefore, by basing the proactive prompts for video scene recording on the premise of safe driving, we can fundamentally prevent the system from interfering with driving due to recommended recording. At the same time, we can also avoid generating low-quality videos that are blurry, shaky, obstructed, or poorly composed, thus ensuring the viewing quality of the final video recording.

[0057] In step S103, if the current road conditions of the target vehicle meet the video recording conditions, a video recording prompt message is generated, and the video recording action is executed upon receiving a confirmation instruction from the user based on the video recording prompt message.

[0058] Among them, performing video recording refers to collecting continuous video stream data through cameras (such as front cameras, rear cameras, DMS (Driver Monitoring System) etc.).

[0059] Specifically, if it is determined that the current road conditions of the target vehicle meet the video recording conditions (e.g., the vehicle speed is less than 100 km / h and the vehicle camera is unobstructed), and the overall popularity score of the target video corresponding to the current coordinates of the target vehicle is greater than a first preset score threshold), then it indicates that the vehicle is about to enter or approach a high-popularity recording scene and the target vehicle meets the video recording conditions. The user can be notified to record a video. Therefore, a video recording prompt message is generated and sent to the user, asking if they wish to perform the video recording action. If the user confirms the recording, the recording will proceed upon receiving the confirmation instruction from the user based on the video recording prompt message. To ensure that each video frame is accurately linked to the current operating status of the target vehicle, the latest road conditions of the target vehicle need to be recorded simultaneously with the video recording. This recording aims to sample and record the target vehicle's current operating status data at a high frequency (e.g., 1-10 times per second) aligned with the video frame timestamps during video recording. After video recording and the latest road condition recording are completed, the data is uploaded to the cloud for storage. This provides a basis for subsequent video editing, updates the video recording database, and enables personalized recommendations for different users, achieving a synergistic effect between video recording and the target vehicle's current operating status.

[0060] Therefore, by anticipating the next exciting scene the vehicle is about to reach, the system proactively issues a prompt before the user may even notice or have time to react, effectively solving the problem of missing highly anticipated recording scenes due to concentration while driving at high speeds.

[0061] Optionally, in one embodiment of this application, performing a video recording action includes: recording the road scene in front of the target vehicle and the road scene on both sides based on a first camera, recording the road scene behind the target vehicle based on a second camera, and recording the user status information inside the target vehicle based on a third camera; combining the road scene in front of the target vehicle and the road scene on both sides, the road scene behind the target vehicle, and the user status information inside the target vehicle into a video composite to obtain the final video recording information, and saving the video parameters of the final video recording information to a video recording database.

[0062] Specifically, in this embodiment, after receiving a confirmation command from the user based on the video recording prompt information, the vehicle camera begins recording. The recording scenarios mainly include recording the road in front of the target vehicle and the road on both sides based on the first camera (front camera), recording the road behind the target vehicle based on the second camera (rear camera), and recording the user status information inside the target vehicle based on the third camera (DMS camera). Alternatively, a photo can be taken every 6 seconds to 10 minutes. The content of the captured images is compared, and the best image is selected for saving. Then, the recorded video is manually synthesized by the user or automatically synthesized by the video editing equipment to obtain a final video recording information. The final video recording information and related video parameters are saved locally or to a video recording database.

[0063] Therefore, upon receiving a confirmation command from the user based on the video recording prompt, the vehicle's camera begins recording. This achieves the best balance between intelligent recommendations and user-initiated decision-making, ensuring driving safety and respecting user wishes. It also avoids privacy leaks and user complaints that may result from fully automatic recording.

[0064] Optionally, in one embodiment of this application, after obtaining the final video recording information and saving the video parameters of the final video recording information to the video recording database, the method further includes: obtaining the latest number of views, the latest number of likes, and the latest number of favorites of the final video recording information based on a preset interface; and updating the new coordinate information corresponding to the final video recording information and the comprehensive popularity score of the video parameters in the video recording database based on the latest number of views, the latest number of likes, and the latest number of favorites of the final video recording information.

[0065] Specifically, after saving the video parameters of the final video recording information to the video recording database, in order to correct and optimize the original video recording database and enable the system to continuously adapt to changing user preferences and popular trends, this embodiment of the application continues to obtain the latest views, likes, and favorites of the final video recording information based on a preset interface. The system updates the new coordinate information and the comprehensive popularity score of the video parameters corresponding to the final video recording information in the video recording database based on the latest views, likes, and favorites. Continuously updating the new coordinate information and the comprehensive popularity score of the video parameters corresponding to the final video recording information in the video recording database also enables the system to have the ability to dynamically learn and continuously optimize, thereby preventing the video recording database from recommending outdated or unpopular video recording scenes due to outdated information, and ensuring that the high-popularity scenes recommended by the system are always the current real popular scenes.

[0066] For example, if a scenic spot along the way becomes a unique view due to seasonal changes or events, and its popularity may surge during a specific period, then during that specific period, the target vehicle can remind the user to record a video when it is about to reach that scene, so as not to miss the specific view. If it is not during this specific period, then the reminder can be ignored when the vehicle is about to reach that scene, that is, there is no need to remind the user to record a video, thus ensuring the quality and real-time nature of the user's video recording.

[0067] Therefore, by updating the video recording database in real time, the system can quickly capture changes in trending scenes and include them in high-popularity recommendations. Conversely, if a scenic spot's popularity drops sharply due to closure or negative news, the system can also promptly lower its recommendation weight, thus ensuring the freshness and relevance of the recommendation results.

[0068] In summary, the video recording method according to the embodiments of this application identifies the current road conditions of the target vehicle when its current coordinates match the coordinates of historically popular recording scenes in the video recording database. Once the current road conditions meet the video recording conditions, a video recording prompt is generated. Upon receiving a confirmation command from the user based on the video recording prompt, the video recording action is executed. This method constructs a popular video recording database and utilizes this database in conjunction with real-time vehicle status to proactively prompt and assist the user in setting optimal parameters for video recording when they are about to reach a high-value scene. Ultimately, this achieves intelligent, contextualized, and high-social-value automatic video acquisition.

[0069] Figure 2 This is a schematic diagram of the structure of a video recording device provided in an embodiment of this application.

[0070] For example, such as Figure 2 As shown, the device may include: an acquisition module 100, an identification module 200, and a video recording module 300.

[0071] The acquisition module 100 is used to acquire the current coordinate information of the target vehicle. The identification module 200 is used to identify the current driving conditions of the target vehicle if the current coordinate information matches the coordinate information of historical high-popularity recording scenes in the pre-built video recording database, and to determine whether the current driving conditions of the target vehicle meet the video recording conditions. The video recording database is dynamically constructed based on the historical video recording information of other vehicle users and the video feedback information of preset social platforms. The video recording module 300 is used to generate a video recording prompt message if the current driving conditions of the target vehicle meet the video recording conditions, and to execute the video recording action upon receiving a confirmation instruction from the user based on the video recording prompt message.

[0072] Optionally, in one embodiment of this application, before obtaining the current coordinate information of the target vehicle, the acquisition module 100 further includes: The acquisition unit is used to acquire historical video recording information from other vehicle users and / or video feedback information from preset social media platforms; The identification unit is used to identify the first position coordinates of historical video recording information and / or the second position coordinates of video feedback information based on a preset interface. The construction unit is used to obtain the coordinate information of historically popular recording scenes based on the first position coordinates and / or the second position coordinates, and to construct a video recording database based on the coordinate information of historically popular recording scenes.

[0073] Optionally, in one embodiment of this application, the identification module 200 includes: The matching unit is used to match the corresponding target video from the video recording database based on the current coordinate information of the target vehicle; The calculation unit is used to calculate the overall popularity score of the target video; The first determination unit is used to determine whether the overall popularity score is greater than the first preset score threshold. If the overall popularity score is greater than the first preset score threshold, it is determined that the current coordinate information matches the coordinate information of historical high-popularity recording scenes in the video recording database. If the overall popularity score is less than or equal to the first preset score threshold, it is determined that the current coordinate information does not match the coordinate information of historical high-popularity recording scenes in the video recording database.

[0074] Optionally, in one embodiment of this application, the computing unit includes: The first acquisition subunit is used to acquire the current number of views, current number of likes, and current number of favorites of the target video; The calculation subunit is used to calculate the first product of the current number of views and the first weight coefficient, the second product of the current number of likes and the second weight coefficient, and the third product of the current number of favorites and the third weight coefficient. The second acquisition subunit is used to obtain the comprehensive popularity score of the target video based on the first product, the second product, and the third product.

[0075] Optionally, in one embodiment of this application, the identification module 200 includes: The judgment unit is used to determine whether the speed information of the target vehicle is within the preset speed range and whether the camera of the target vehicle is in an unobstructed state. The second determination unit is used to determine that the current driving conditions of the target vehicle meet the video recording conditions if the vehicle speed information is within a preset speed range and the camera is unobstructed.

[0076] Optionally, in one embodiment of this application, the video recording module 300 includes: The video recording unit is used to record the road scene in front of the target vehicle and the road scene on both sides based on the first camera, and to record the road scene behind the target vehicle based on the second camera, and to record the user status information inside the target vehicle based on the third camera. The video synthesis unit is used to synthesize the road scenes in front of the target vehicle and the roads on both sides, the road scene behind the target vehicle, and the user status information inside the target vehicle to obtain the final video recording information and save the video parameters of the final video recording information to the video recording database.

[0077] Optionally, in one embodiment of this application, after obtaining the final video recording information and saving the video parameters of the final video recording information to the video recording database, the video synthesis unit further includes: The third acquisition subunit is used to obtain the latest number of views, the latest number of likes, and the latest number of favorites of the final video recording information based on a preset interface. The update sub-unit is used to update the new coordinate information and video parameters corresponding to the final video recording information in the video recording database based on the latest views, likes, and favorites of the final video recording information.

[0078] In summary, the video recording device according to the embodiments of this application identifies the current driving conditions of the target vehicle when its current coordinates match the coordinates of historically popular recording scenes in the video recording database. Once the current driving conditions of the target vehicle meet the video recording conditions, a video recording prompt is generated. Upon receiving a confirmation command from the user based on the video recording prompt, the video recording action is executed. This method constructs a popular video recording database and utilizes this database in conjunction with real-time vehicle status to proactively prompt and assist the user in setting optimal parameters for video recording when they are about to reach a high-value scene, thereby ultimately achieving intelligent, contextualized, and high-social-value automatic video acquisition.

[0079] Figure 3 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application.

[0080] It should be understood that the methods described above can be applied to... Figure 3 In the vehicle with the structure shown.

[0081] Furthermore, this application also protects an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform the video recording method provided in this application.

[0082] Furthermore, the device also includes a communication interface 303 for communication between the memory 301 and the processor 302.

[0083] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0084] It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0085] It should be understood that the apparatus provided in this embodiment is used to perform the video recording method described above, and therefore can achieve the same effect as the above implementation method.

[0086] When using an integrated unit, the device may include a processing module and a storage module. When the device is applied to a vehicle, the processing module can be used to control and manage the vehicle's movements. The storage module can be used to support the vehicle in executing program code, etc.

[0087] The processing module may be a processor 302 or a controller, which may implement or execute various exemplary logic blocks, modules, and circuits as disclosed herein. The processor 302 may also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory 301.

[0088] In addition, the device provided in the embodiments of this application may specifically be a chip, component or module. The chip may include a connected processor 302 and a memory 301. The memory 301 is used to store instructions. When the processor calls and executes the instructions, the chip can execute the video recording method provided in the above embodiments.

[0089] This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the above-described related method steps to implement a video recording method provided in the above embodiment.

[0090] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement a video recording method provided in the above embodiment.

[0091] In this embodiment, the device, computer-readable storage medium, computer program product, or chip are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0092] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0093] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only 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 device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0094] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A video recording method characterized by, The method comprises: obtaining current coordinate information of a target vehicle; if the current coordinate information matches historical high-heat recording scene coordinate information in a pre-constructed video recording database, identifying the current driving road condition of the target vehicle, and determining whether the current driving road condition of the target vehicle meets a video recording condition, wherein the video recording database is dynamically constructed based on historical video recording information of other vehicle users and video feedback information of a preset social platform; if the current driving road condition of the target vehicle meets the video recording condition, generating video recording prompt information, and executing a video recording action upon receiving a confirmation instruction issued by a user based on the video recording prompt information.

2. The method of claim 1, wherein, Before obtaining the current coordinate information of the target vehicle, the method further comprises: obtaining historical video recording information of the other vehicle users and / or video feedback information of the preset social platform; identifying first position coordinates of the historical video recording information and / or second position coordinates of the video feedback information based on a preset interface; based on the first position coordinates and / or the second position coordinates, obtaining the historical high-heat recording scene coordinate information, and constructing the video recording database based on the historical high-heat recording scene coordinate information.

3. The method of claim 1, wherein, Determining whether the current coordinate information matches historical high-heat recording scene coordinate information in a pre-constructed video recording database comprises: based on the current coordinate information of the target vehicle, matching a corresponding target video from the video recording database; calculating a comprehensive heat score of the target video; determining whether the comprehensive heat score is greater than a first preset score threshold, if the comprehensive heat score is greater than the first preset score threshold, determining that the current coordinate information matches the historical high-heat recording scene coordinate information in the video recording database, if the comprehensive heat score is less than or equal to the first preset score threshold, determining that the current coordinate information does not match the historical high-heat recording scene coordinate information in the video recording database.

4. The method of claim 3, wherein, The calculation of the comprehensive heat score of the target video comprises: obtaining the current view count, the current like count and the current collection count of the target video; calculating a first product of the current view count and a first weight coefficient, a second product of the current like count and a second weight coefficient, and a third product of the current collection count and a third weight coefficient; obtaining the comprehensive heat score of the target video according to the first product, the second product and the third product.

5. The method of claim 1, wherein, The determination of whether the current driving road condition of the target vehicle meets the video recording condition comprises: determining whether the vehicle speed information of the target vehicle is in a preset vehicle speed interval, and determining whether the camera of the target vehicle is in an unobstructed state; if the vehicle speed information is in the preset vehicle speed interval and the camera is in the unobstructed state, determining that the current driving road condition of the target vehicle meets the video recording condition.

6. The method of claim 1, wherein, The execution of the video recording action comprises: record a front road and two side road scenes of the target vehicle based on a first camera, record a rear road scene of the target vehicle based on a second camera, and record user state information inside the target vehicle based on a third camera; video synthesis is performed on the front road and two side road scenes of the target vehicle, the rear road scene of the target vehicle, and the user state information inside the target vehicle to obtain final video recording information, and video parameters of the final video recording information are saved to a video recording database.

7. The method of claim 6, wherein, After obtaining the final video recording information and saving the video parameters of the final video recording information to the video recording database, the method further includes: obtaining a latest view count, a latest like count, and a latest collection count of the final video recording information based on a preset interface; updating a comprehensive hotness score of new coordinate information and video parameters corresponding to the final video recording information in the video recording database based on the latest view count, the latest like count, and the latest collection count of the final video recording information.

8. A video recording apparatus, characterized by comprising: The apparatus includes: an obtaining module configured to obtain current coordinate information of a target vehicle; an identifying module configured to identify a current driving road condition of the target vehicle and determine whether the current driving road condition of the target vehicle meets a video recording condition if the current coordinate information matches historical high hotness recording scene coordinate information pre-constructed in a video recording database, wherein the video recording database is dynamically constructed based on historical video recording information of other vehicle users and video feedback information of a preset social platform; a video recording module configured to generate a video recording prompt information if the current driving road condition of the target vehicle meets the video recording condition, and perform a video recording action if a confirmation instruction issued by a user based on the video recording prompt information is received.

9. A vehicle characterized by comprising: comprise: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the video recording method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program which, when executed, implements the method of any one of claims 1 to 7.

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