Automobile Vlog video generation method and device, vehicle and computer program product

Abstract

The invention relates to the technical field of vehicles, in particular to an automobile Vlog video generation method and device, a vehicle and a computer program product, and the method comprises the steps: obtaining real-time image data collected by a vehicle-mounted sensor, and recognizing a key event and a key scene in the real-time image data; generating a logic framework of video editing according to the identified key event and key scene, and generating an editing instruction of the Vlog video through a preset intelligent video editing algorithm based on the logic framework; and automatically editing and rendering the key event and the key scene according to the editing instruction to generate a target Vlog video. Therefore, the problems of low video production efficiency and low automation degree of a vehicle-mounted video generation scheme in related technologies are solved, the video generation efficiency is improved, the video content is enriched, the continuity and narrative property of the video content are ensured, and the user experience is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a method, device, vehicle and computer program product for generating a car Vlog video. Background Art

[0002] With the rapid development of intelligent connected car technology, in-vehicle image creation technology has become an important branch of this field. This technology uses the in-vehicle camera to capture the environment around the vehicle, and uses advanced image processing and video rendering technology to generate video content with the vehicle driving as the main body. This technology not only enhances the driving experience, but also provides a new content form for the car entertainment system.

[0003] In the field of vehicle-mounted image creation technology, there are already a number of technologies that have achieved the capture of vehicle environments and video generation. The following are some key prior arts related to this application involving the processing of images captured by vehicle-mounted cameras or driving recorders to reduce the complexity of video production and improve efficiency. For example, a method and system for generating a vehicle-mounted short video vlog with one click, as well as a method, device, electronic device and vehicle for generating short videos in a vehicle are proposed in the related art. This technology solves the problem of occlusion of driving scene images captured by the vehicle-mounted camera system through collaborative creation of multiple vehicles, thereby improving the effect of short video generation.

[0004] Although the existing vehicle-mounted image creation technology has made some progress in vehicle environment capture and video generation, it still has some defects and shortcomings:

[0005] The method and system for generating in-vehicle short video vlogs with one click provided in the related art mainly rely on the camera of a single vehicle, which limits the diversity and comprehensiveness of the video content, and the method, device, electronic device and vehicle for generating in-vehicle short videos in the related art solve the problem of occlusion of the driving scene images taken by the in-vehicle camera system through multi-vehicle collaborative creation, but this solution depends on the size and collaborative efficiency of the fleet, and may not be applicable to individual vehicles or small fleets. And although the existing technology provides the function of video generation, it is not convenient enough in terms of social sharing, and users need additional operations to share video content, which is not safe or convenient during driving.

[0006] To sum up, although the existing technology has achieved certain achievements in the field of in-vehicle image creation, it still needs to be improved in terms of video production efficiency, perspective diversity, image occlusion processing, and convenience of social sharing. Summary of the invention

[0007] The present application provides a method, device, vehicle and computer program product for generating a car Vlog video to solve the problems of low video production efficiency, low degree of automation and inconvenient social sharing in the vehicle video generation solution in the related art.

[0008] The first aspect of the present application provides a method for generating a car Vlog video, comprising the following steps: acquiring real-time image data collected by a vehicle-mounted sensor, and identifying key events and key scenes in the real-time image data; generating a logical framework for video editing according to the identified key events and key scenes, and based on the logical framework, generating editing instructions for the Vlog video through a preset intelligent video editing algorithm; automatically editing and rendering the key events and the key scenes according to the editing instructions to generate a target Vlog video.

[0009] Optionally, generating a logical framework of a video clip based on the identified key events and key scenes includes: determining the time sequence, scene switching and transition effects of the key events and the key scenes; assigning timestamps to the key events and determining the relevance between the key events and the key scenes; generating a logical framework of the video clip based on the time sequence, scene switching, transition effects, timestamps and relevance between the key events and the key scenes.

[0010] Optionally, when the key events and the key scenes are automatically edited and rendered according to the editing instructions, it includes: editing the key events and the key scenes in sequence according to the editing instructions, and constructing an initial Vlog video; rendering the initial Vlog video using video encoding technology, and adding at least one multimedia element to the rendered Vlog video to obtain the target Vlog video.

[0011] Optionally, the identifying key events and key scenes in the real-time image data includes: determining key features in the real-time image data based on preset rules; and using computer vision technology to identify key features in the real-time image data to obtain the key events and the key scenes.

[0012] Optionally, before acquiring the real-time image data collected by the vehicle-mounted sensor, the method includes: acquiring initial image data collected by the vehicle-mounted sensor; and performing image preprocessing on the initial image data using image processing technology to obtain the real-time image data.

[0013] Optionally, after generating the target Vlog video, the method includes: receiving a sharing instruction from a user; and uploading the target Vlog video to one or more video sharing platforms based on the sharing instruction.

[0014] The second aspect of the present application provides a device for generating a car Vlog video, including: an identification module, used to obtain real-time image data collected by vehicle-mounted sensors, and identify key events and key scenes in the real-time image data; a generation module, used to generate a logical framework for video clips according to the identified key events and key scenes, and based on the logical framework, generate editing instructions for the Vlog video through a preset intelligent video editing algorithm; an editing module, used to automatically edit and render the key events and the key scenes according to the editing instructions to generate a target Vlog video.

[0015] Optionally, the generation module is used to: determine the time sequence, scene switching and transition effects of the key events and the key scenes; assign timestamps to the key events and determine the relevance between the key events and the key scenes; and generate a logical framework of the video clip based on the time sequence, scene switching, transition effects, timestamps and relevance between the key events and the key scenes.

[0016] Optionally, when the key events and the key scenes are automatically edited and rendered according to the editing instructions, the editing module is also used to: edit the key events and the key scenes in sequence according to the editing instructions, and construct an initial Vlog video; render the initial Vlog video using video encoding technology, and add at least one multimedia element to the rendered Vlog video to obtain the target Vlog video.

[0017] Optionally, the recognition module is further used to: determine the key features in the real-time image data based on preset rules; and use computer vision technology to identify the key features in the real-time image data to obtain the key events and the key scenes.

[0018] Optionally, before acquiring the real-time image data collected by the vehicle-mounted sensor, the recognition module is further used to: acquire the initial image data collected by the vehicle-mounted sensor; and perform image preprocessing on the initial image data using image processing technology to obtain the real-time image data.

[0019] Optionally, after generating the target Vlog video, the editing module is further used to: receive a sharing instruction from a user; and upload the target Vlog video to one or more video sharing platforms based on the sharing instruction.

[0020] The third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for generating a car Vlog video as described in the above embodiment.

[0021] The fourth aspect of the present application provides a computer program product on which a computer program is stored, and the program is executed by a processor to implement the method for generating a car Vlog video as described in the above embodiment.

[0022] In the above implementation, real-time image data collected by the vehicle-mounted sensor is obtained, and key events and key scenes in the real-time image data are identified. A logical framework for video editing is generated based on the identified key events and key scenes, and based on the logical framework, editing instructions for the Vlog video are generated through a preset intelligent video editing algorithm. The key events and key scenes are automatically edited and rendered according to the editing instructions to generate the target Vlog video. In this way, the problems of insufficient video production efficiency, low degree of automation, and inconvenient social sharing in the vehicle-mounted video generation solution in the related art are solved, the efficiency of video generation is improved, the video content is enriched, the coherence and narrative of the video content are ensured, and the user experience is improved. In addition, the system can adapt to different driving environments and scenes, flexibly adjust the shooting and editing strategies, and ensure that high-quality video content can be generated under various conditions.

[0023] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0025] Figure 1 A flowchart of a method for generating a car Vlog video according to an embodiment of the present application;

[0026] Figure 2 Schematic diagram of the structure of a system for generating a car Vlog video according to an embodiment of the present application;

[0027] Figure 3 Flow chart of a method for generating a car Vlog video according to an embodiment of the present application;

[0028] Figure 4 This is an example diagram of a device for generating a car Vlog video according to an embodiment of the present application;

[0029] Figure 5 It is a schematic diagram of a vehicle structure according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0031] The following describes the method, device, vehicle and computer program product for generating a car Vlog video in the embodiment of the present application with reference to the accompanying drawings. In view of the problems that the video production efficiency of the vehicle-mounted video generation scheme in the related art mentioned in the above background technology is not high enough, the degree of automation is low, and social sharing is not convenient, the present application provides a method for generating a car Vlog video, in which real-time image data collected by the vehicle-mounted sensor is obtained, and the key events and key scenes in the real-time image data are identified, and a logical framework of video clips is generated according to the identified key events and key scenes, and based on the logical framework, the editing instructions of the Vlog video are generated by a preset intelligent video editing algorithm, and the key events and key scenes are automatically edited and rendered according to the editing instructions to generate a target Vlog video. Thus, the problems that the video production efficiency of the vehicle-mounted video generation scheme in the related art is not high enough, the degree of automation is low, and social sharing is not convenient are solved, the efficiency of video generation is improved, the video content is enriched, the coherence and narrative of the video content are ensured, and the user experience is improved. In addition, the system can adapt to different driving environments and scenes, flexibly adjust the shooting and editing strategies, and ensure that high-quality video content can be generated under various conditions.

[0032] Specifically, Figure 1 A flowchart of a method for generating a car Vlog video provided in an embodiment of the present application.

[0033] Before specifically introducing the method for generating a car Vlog video, a brief introduction to the modules involved in this application is given, such as Figure 2 As shown, they are environment perception module, image data acquisition and event recognition module, video editing logic framework generation module, intelligent video editing algorithm processing module, video automatic editing and rendering module, among which,

[0034] The environment perception module is used to analyze the vehicle driving environment in real time to obtain real-time image data;

[0035] The image data acquisition and event recognition module is used to determine the key features of video shooting according to the vehicle driving environment and scene, obtain the real-time image data captured by the vehicle camera, and recognize the key events and key scenes in the vehicle driving according to the image data;

[0036] The video clip logic framework generation module is used to generate the logic framework of the video clip according to the identified key events and key scenes;

[0037] The intelligent video editing algorithm processing module is used to process the logical framework through a preset intelligent video editing algorithm, and use the output of the intelligent video editing algorithm as the editing instruction for generating the Vlog video;

[0038] The video automatic editing and rendering module is used to automatically edit and render videos of key events and key scenes according to editing instructions to generate narrative Vlog video content;

[0039] The user interaction and sharing module is used to share the Vlog video content to the video sharing platform according to the user's selection.

[0040] Furthermore, the method for generating the car Vlog video includes the following steps:

[0041] In step S101, real-time image data collected by vehicle-mounted sensors is acquired, and key events and key scenes in the real-time image data are identified.

[0042] Optionally, in some embodiments, before acquiring the real-time image data collected by the vehicle-mounted sensor, the method includes: acquiring initial image data collected by the vehicle-mounted sensor; and performing image preprocessing on the initial image data using image processing technology to obtain real-time image data.

[0043] Specific as Figure 3 As shown in the figure, during the driving process of the vehicle, the on-board sensors (such as cameras, radars, lidars, etc.) will continuously collect data about the surrounding environment, including images, videos, etc. The vehicle needs to establish a communication connection with the on-board sensors, receive the data sent by the on-board sensors in real time, and use image processing technology to pre-process the initial image data to obtain real-time image data, including the following processing methods:

[0044] (1) Denoising

[0045] The initial image data may contain various noises, such as Gaussian noise, salt and pepper noise, etc. Filtering techniques such as mean filtering, median filtering, Gaussian filtering, etc. can be used to remove these noises, which can effectively smooth the image and reduce the impact of noise on image quality.

[0046] (2) Enhanced processing

[0047] Due to the limitations of lighting conditions, sensor performance and other factors, the initial image data may have problems such as insufficient brightness and insufficient contrast. Histogram equalization, contrast stretching and other technologies can be used to enhance the visual effect of the image, and the brightness and contrast of the image can be adjusted to make the image clearer and easier to identify.

[0048] (3) Edge detection and extraction

[0049] In intelligent driving systems, edge information is an important basis for identifying obstacles such as vehicles and pedestrians. Therefore, it is necessary to perform edge detection and extraction on the initial image data. Commonly used edge detection algorithms include Canny operator, Sobel operator, Prewitt operator, etc. These algorithms can accurately detect edge information in images and provide strong support for subsequent target recognition.

[0050] (4) Other treatments

[0051] In addition to the above processing, other image processing operations can be performed according to actual needs, such as image cropping, scaling, rotation, etc. These operations can further meet the needs of the intelligent driving system for image data.

[0052] After being processed by the above image processing technology, the initial image data is converted into clearer and more accurate real-time image data. These real-time image data can provide more reliable environmental information for the intelligent driving system and improve the safety and reliability of the intelligent driving system.

[0053] Optionally, in some embodiments, the identifying key events and key scenes in the real-time image data includes: determining key features in the real-time image data based on preset rules; and using computer vision technology to identify key features in the real-time image data to obtain key events and key scenes.

[0054] Among them, the preset rules may include setting objects within a preset specific size or shape range as key features, setting a specific motion trajectory or speed as a key feature, setting specific character features as key features, setting specific scene layouts or elements as key features, and setting specific spatial positions or areas as key features.

[0055] For example, the layout or building features of a specific area (such as a park or square) can be set as key features, large vehicles (such as trucks or buses) or objects of specific shapes (such as circles or squares) can be set as key features, intersections, highway entrances and other locations can be set as key features, and so on.

[0056] It should be understood that the real-time analysis of the vehicle's driving environment to determine the key features of the video shooting is achieved through the environmental perception module, which integrates the on-board sensor data, such as lidar, ultrasonic sensors and cameras, to build a comprehensive understanding of the surrounding environment. Using computer vision technology to identify key features, such as traffic signs, pedestrians and other vehicles, the decision algorithm further selects key scenes and key events worth recording based on the key features, laying the foundation for subsequent video shooting.

[0057] Specifically, after the key features are determined, the system will start the on-board camera to capture real-time image data, which will be processed by the on-board computing unit to identify key events and key feature scenes in the vehicle's driving. The event recognition algorithm uses image processing and machine learning techniques, such as convolutional neural networks, to identify and mark key events such as traffic accidents, emergencies and scenic spots.

[0058] In step S102, a logical framework of video clips is generated according to the identified key events and key scenes, and based on the logical framework, editing instructions for the Vlog video are generated through a preset intelligent video editing algorithm.

[0059] Optionally, in some embodiments, a logical framework of a video clip is generated based on the identified key events and key scenes, including: determining the time sequence, scene switching and transition effects of the key events and key scenes; assigning timestamps to key events and determining the relevance of key events and key scenes; generating a logical framework of a video clip based on the time sequence, scene switching, transition effects, timestamps and relevance of key events and key scenes.

[0060] After identifying key events and key scenes, the system generates a logical framework for the video clip. This step involves building the narrative structure of the video, including the chronological order of events, scene switching, and transition effects. The system assigns a timestamp to each key event and analyzes the correlation between key events to determine how to connect different key scenes together to form a coherent narrative flow.

[0061] In step S103, key events and key scenes are automatically edited and rendered according to the editing instructions to generate a target Vlog video.

[0062] Optionally, in some embodiments, when key events and key scenes are automatically edited and rendered according to editing instructions, it includes: editing key events and key scenes in sequence according to the editing instructions, and constructing an initial Vlog video; rendering the initial Vlog video using video encoding technology, and adding at least one multimedia element to the rendered Vlog video to obtain a target Vlog video.

[0063] After generating the logical framework, the system will apply the intelligent video editing algorithm for processing. Based on machine learning and artificial intelligence technology, the algorithm automatically analyzes the logical framework and generates corresponding editing instructions, including editing decisions, selection of transition effects, and audio synchronization. The algorithm outputs a series of editing instructions to guide the subsequent video editing and rendering process.

[0064] Finally, the system organizes key events and key scenes in order according to the editing instructions to construct the initial Vlog video, and automatically edits and renders the initial Vlog video to generate narrative Vlog video content. The automatic editing process extracts the required clips and arranges them in the order of the logical framework. Video rendering uses efficient video encoding technology to optimize video quality and ensure smooth playback on different devices. In addition, the system obtains the target Vlog video by adding at least one multimedia element such as subtitles, narration or background music to enhance the narrative and attractiveness of the video.

[0065] Optionally, in some embodiments, after generating the target Vlog video, the method includes: receiving a sharing instruction from a user; and uploading the target Vlog video to one or more video sharing platforms based on the sharing instruction.

[0066] After confirming that the Vlog video effect is correct, the user can click the "Share" button in the software to trigger the sharing function. At this time, the software will pop up a sharing settings interface, where the user can select the video sharing platform they want to share and set related sharing parameters, such as title, description, tags, etc. After these settings are completed, the user clicks the "Confirm Sharing" button, and the software will receive the user's sharing instructions.

[0067] If the user selects multiple video sharing platforms, the software will upload the video to each platform in turn. During the upload process, the software will use the API interface or SDK of each platform for identity authentication and file transfer.

[0068] After the video is uploaded, the software will provide feedback to the user on the sharing result. If the upload is successful, the software will display the corresponding success prompt message and may provide a link or QR code to access the video on the target platform. If the upload fails, the software will display an error message and allow the user to retry uploading or choose other sharing methods.

[0069] According to the method for generating a car Vlog video proposed in the embodiment of the present application, real-time image data collected by the vehicle-mounted sensor is obtained, and key events and key scenes in the real-time image data are identified. A logical framework for video editing is generated according to the identified key events and key scenes, and based on the logical framework, the editing instructions of the Vlog video are generated by a preset intelligent video editing algorithm, and the key events and key scenes are automatically edited and rendered according to the editing instructions to generate the target Vlog video. Thus, the problems of low video production efficiency, low degree of automation, and inconvenient social sharing in the vehicle-mounted video generation scheme in the related art are solved. Compared with the prior art, the user experience is significantly improved. By simplifying the operation process, users can easily generate and share short videos with one click, making the vehicle-mounted entertainment system more social and convenient for users to share wonderful moments during driving with others. The system realizes the fusion of multi-perspective images through the integration of multiple sensor devices, enhances the richness and viewing of video content, and provides users with a more comprehensive and three-dimensional driving experience. The speed and accuracy of video processing are improved, and a large amount of video data is effectively processed.

[0070] Next, a device for generating a car Vlog video according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0071] Figure 4 It is a block diagram of a device for generating a car Vlog video according to an embodiment of the present application.

[0072] like Figure 4 As shown, the device 10 for generating the automobile Vlog video includes: a recognition module 100 , a generation module 200 and an editing module 300 .

[0073] Among them, the recognition module 100 is used to obtain real-time image data collected by the vehicle-mounted sensor and identify key events and key scenes in the real-time image data; the generation module 200 is used to generate a logical framework for video editing according to the identified key events and key scenes, and based on the logical framework, generate editing instructions for the Vlog video through a preset intelligent video editing algorithm; the editing module 300 is used to automatically edit and render key events and key scenes according to the editing instructions to generate a target Vlog video.

[0074] Optionally, in some embodiments, the generation module 200 is used to: determine the time sequence, scene switching and transition effects of key events and key scenes; assign timestamps to key events and determine the relevance of key events and key scenes; generate a logical framework of video clips based on the time sequence, scene switching, transition effects, timestamps and relevance of key events and key scenes.

[0075] Optionally, in some embodiments, when key events and key scenes are automatically edited and rendered according to editing instructions, the editing module 300 is also used to: edit key events and key scenes in sequence according to the editing instructions, and construct an initial Vlog video; render the initial Vlog video using video encoding technology, and add at least one multimedia element to the rendered Vlog video to obtain a target Vlog video.

[0076] Optionally, in some embodiments, the recognition module 100 is further used to: determine key features in the real-time image data based on preset rules; and use computer vision technology to identify key features in the real-time image data to obtain key events and key scenes.

[0077] Optionally, in some embodiments, before acquiring the real-time image data collected by the vehicle-mounted sensor, the recognition module 100 is further used to: acquire the initial image data collected by the vehicle-mounted sensor; and perform image preprocessing on the initial image data using image processing technology to obtain real-time image data.

[0078] Optionally, in some embodiments, after generating the target Vlog video, the editing module 300 is further used to: receive a sharing instruction from a user; and upload the target Vlog video to one or more video sharing platforms based on the sharing instruction.

[0079] It should be noted that the aforementioned explanation of the embodiment of the method for generating a car Vlog video is also applicable to the device for generating a car Vlog video of this embodiment, and will not be repeated here.

[0080] According to the device for generating car Vlog videos proposed in the embodiment of the present application, real-time image data collected by vehicle-mounted sensors is obtained, and key events and key scenes in the real-time image data are identified. A logical framework for video editing is generated based on the identified key events and key scenes, and based on the logical framework, editing instructions for Vlog videos are generated through a preset intelligent video editing algorithm. Key events and key scenes are automatically edited and rendered according to the editing instructions to generate a target Vlog video. Thus, the problems of insufficient video production efficiency, low degree of automation, and inconvenient social sharing in the vehicle-mounted video generation solution in the related art are solved, the efficiency of video generation is improved, the video content is enriched, the coherence and narrative of the video content are ensured, and the user experience is improved. In addition, the system can adapt to different driving environments and scenes, flexibly adjust shooting and editing strategies, and ensure that high-quality video content can be generated under various conditions.

[0081] Figure 5 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:

[0082] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0083] When the processor 502 executes the program, the method for generating the car Vlog video provided in the above embodiment is implemented.

[0084] Furthermore, the vehicle also includes:

[0085] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0086] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0087] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0088] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0089] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0090] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0091] An embodiment of the present application also provides a computer program product, on which a computer program is stored, and when the program is executed by a processor, the method for generating a car Vlog video as described above is implemented.

[0092] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0093] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0094] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0095] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer program product for use with an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer program product" can be any device that can contain, store, communicate, propagate or transmit a program for use with an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer program products (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). Furthermore, the computer program product may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example by optically scanning the paper or other medium and then editing, interpreting or, if necessary, processing in another suitable manner, and then storing it in a computer memory.

[0096] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0097] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer program product, which, when executed, includes one or a combination of the steps of the method embodiment.

[0098] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer program product.

[0099] The computer program product mentioned above may be a read-only memory, a disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for generating a car Vlog video, characterized in that: The following steps are involved: Acquire real-time image data collected by vehicle-mounted sensors, and identify key events and key scenes in the real-time image data; Generate a logical framework of video editing according to the identified key events and key scenes, and based on the logical framework, generate editing instructions for the Vlog video through a preset intelligent video editing algorithm; The key events and the key scenes are automatically edited and rendered according to the editing instructions to generate a target Vlog video.

2. The method according to claim 1, characterized in that: The logic framework for generating video clips based on the identified key events and key scenes includes: Determine the time sequence, scene switching and transition effects of the key events and the key scenes; Assigning a timestamp to the key event and determining the relevance of the key event to the key scene; A logical framework of the video clip is generated according to the time sequence, scene switching, transition effects, timestamps and relevance of the key events and the key scenes.

3. The method according to claim 1, characterized in that: When the key events and the key scenes are automatically edited and rendered according to the editing instructions, it includes: Editing the key events and the key scenes in sequence according to the editing instructions, and constructing an initial Vlog video; The initial Vlog video is rendered using video encoding technology, and at least one multimedia element is added to the rendered Vlog video to obtain the target Vlog video.

4. The method according to claim 1, characterized in that: The identifying key events and key scenes in the real-time image data includes: Determining key features in the real-time image data based on preset rules; Computer vision technology is used to identify key features in the real-time image data to obtain the key events and the key scenes.

5. The method according to claim 1, characterized in that Before obtaining real-time image data collected by vehicle-mounted sensors, including: Acquiring initial image data collected by the vehicle-mounted sensor; The initial image data is preprocessed using image processing technology to obtain the real-time image data.

6. The method according to claim 1, characterized in that After generating the target Vlog video, including: Receive sharing instructions from users; The target Vlog video is uploaded to one or more video sharing platforms based on the sharing instruction.

7. A device for generating a car Vlog video, characterized in that: include: An identification module, used to obtain real-time image data collected by vehicle-mounted sensors and identify key events and key scenes in the real-time image data; A generation module, used to generate a logical framework of video clips according to the identified key events and key scenes, and based on the logical framework, generate editing instructions for the Vlog video through a preset intelligent video editing algorithm; The editing module is used to automatically edit and render the key events and the key scenes according to the editing instructions to generate a target Vlog video.

8. The device according to claim 7, characterized in that The generating module is used for: Determine the time sequence, scene switching and transition effects of the key events and the key scenes; Assigning a timestamp to the key event and determining the relevance of the key event to the key scene; A logical framework of the video clip is generated according to the time sequence, scene switching, transition effects, timestamps and relevance of the key events and the key scenes.

9. A vehicle, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for generating a car Vlog video as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for generating a car Vlog video as described in any one of claims 1 to 6 is implemented.

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