74 results about "Video optimization" patented technology

The invention relates to the technical field of video optimization, and discloses a video content adaptive optimization system based on deep learning, which comprises a video extraction module, a video decoding module, a coding adjustment module, a video backtracking module and a video evaluation module, the video extraction module is configured to obtain video feature data according to the motion complexity feature vector, the scene switching feature vector and the texture feature vector, and the video decoding module is configured to decode the video feature data based on an initial deep learning model to obtain video adjustment parameters. The coding adjustment module is configured to obtain a first output video, the video backtracking module is configured to obtain a target deep learning model and obtain a second output video based on a first output video adjustment parameter, and the video evaluation module is configured to judge whether the video quality of the second output video reaches the standard or not; and if not, obtaining a third output video according to the historical input video adjustment parameters. The method provided by the invention has the characteristics of good adaptability and optimization for different input videos.

The invention relates to the technical field of semantic analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a video generation method, device and equipment based on text information and a medium, and the method comprises the steps: obtaining original text data, carrying out semantic structure analysis on the original text data, and generating a semantic classification result and key information; matching a corresponding video template from a preset video template set based on the semantic classification result, wherein the video template comprises a predefined material filling strategy; selecting a target material from a material library based on the key information; filling the target material into the video template to generate a basic video; performing video optimization processing on the basic video to generate a target video; and outputting the target video. According to the method, the visual and audio materials are selected from the material library by combining semantic structure analysis and key information extraction of the text, and the video content is generated based on the preset video template filling, so that the video generation effect and the content expression accuracy are improved.

The invention relates to the field of data management, in particular to a community data management system for an intelligent old-age care community, and the system comprises a video monitoring unit which comprises a plurality of community monitoring devices and is used for collecting monitoring videos of all monitoring areas; the video analysis unit is used for periodically determining the video frame category of each basic video frame according to the personnel change reference value and the personnel influence reference value of the basic video frame corresponding to the community monitoring equipment; the video optimization unit is used for determining the state of the monitoring equipment according to the first-class video frame proportion and the first-class video frame density corresponding to the community monitoring equipment, and determining a corresponding video frame optimization mode as compensation optimization or activity feature optimization according to the state of the monitoring equipment; the key frame optimization unit is used for determining a processing mode to supplement or generate image description for the associated frame according to the effective state; and the monitoring data processing efficiency is improved.

The invention provides a method for generating a dynamic three-dimensional Gaussian scene based on an image of a diffusion model. The method comprises the following steps: S1, generating a static three-dimensional Gaussian scene; s2, generating a dynamic video: generating the dynamic video according to the input image by using a stable video diffusion model; s3, optimizing video quality: processing the dynamic video frame by frame by using a diffusion model, and obtaining an optimized dynamic video image through back propagation; and S4, generating a dynamic three-dimensional Gaussian scene: combining a six-way feature plane (Hexplane) and three-dimensional Gaussian splashing as dynamic scene representation, extracting features from the dynamic scene representation, and introducing a multi-layer perceptron decoder to regress displacement, rotation and zooming information of three-dimensional Gaussian, thereby obtaining the dynamic three-dimensional Gaussian scene. According to the method, the diffusion model and the three-dimensional Gaussian splash are combined for use, the diffusion model is used for strengthening the time correlation and the detail quality, and the problem of low rendering speed is solved based on the three-dimensional Gaussian splash by using the explicit characteristic and the advantages of high efficiency and micro rendering.

The present invention discloses a security monitoring video optimized transmission method and a video monitoring terminal, which relates to the field of video monitoring technology, and includes the following steps: extracting the current frame and the previous frame from a continuous monitoring video frame sequence, and then extracting two adjacent frames of images from the video stream to provide basic data for subsequent dynamic change analysis; pre-processing the extracted two adjacent frames of images, using image difference technology to calculate the difference between the two adjacent frames of images, and generating a differential image through pixel-level comparison. The present invention extracts features such as motion intensity and change density by pre-processing and differential calculation of two adjacent frames of images, and inputs a deep learning model to analyze dynamic changes, and divides the scene into fast and normal dynamic changes. An initial compression algorithm is used for normal scenes, and the bit rate is dynamically adjusted for fast dynamic scenes to ensure the capture of details and balance video quality and compression efficiency, thereby improving the performance and practicality of the monitoring system.

Data encryption and Human Pose Estimation based on imaging a body segment. A key for encrypting a data file is generated based on image data that represent a unique biometric feature of a body segment of a user or motion of the user. An image engine executes artificial intelligence to identify matching image data for decrypting the data file. The image engine is further trained to predict changes in image data due to aging, stress, and the like. An avatar associated with the user, which is generated based on a movement pattern of the user, is configurable for generating an encryption key and for use in an avatar-based language.

The invention discloses an intersection traffic violation total factor snapshot system based on multi-view collaboration, and relates to the technical field of intelligent traffic, and the system comprises a data collection and transmission module, a data preprocessing and splicing module, a data optimization and analysis module, a traffic violation judgment module, and a data storage and management module. According to the invention, through a panoramic video optimization unit in the data optimization and analysis module, the spliced panoramic video is deeply optimized, and tiny splicing traces or image local distortion generated in the splicing process is further eliminated, so that the panoramic video picture is clearer, smoother and more real, and high-quality image materials are provided for subsequent analysis; and the target in the video is accurately recognized through the image recognition and analysis unit, target feature information of vehicles, pedestrians and traffic signs and marked lines is extracted, traffic illegal behaviors can be more accurately judged based on the information, and the situations of misjudgment and missed judgment are reduced.

Methods and systems provide dynamic adjustments for video optimization in a communication session. In one embodiment, the system receives, at a server, an outgoing video stream from a transmitting device to a receiving device; identifies a first set of video parameter data corresponding to the quality of the outgoing video stream; receives, from the receiving device, a second set of video parameter data corresponding to the quality of the video stream; determines one or more quality discrepancies between the first set of video parameter data and the second set of video parameter data; and provides notification of at least a subset of the quality discrepancies to one or both of the transmitting device and the receiving device.

The invention discloses an audio and video synchronous transmission system and method of an HDMI (High Definition Multimedia Interface), and particularly relates to the technical field of transmission, comprising an interface equipment configuration and identification module, an audio and video data acquisition module, an audio and sound quality evaluation module, a video image quality evaluation module, an audio and video optimization processing module and an audio and video synchronous precision analysis module, according to the invention, the audio and video signals of the ultra-high-definition video are obtained through the audio acquisition circuit and the video acquisition chip, and the audio and video quality is comprehensively evaluated based on the frequency response deviation degree, the dynamic range, the definition, the dynamic contrast ratio and the color rendition degree. And the audio or video frame with poor quality is optimized through the audio optimization unit and the ultra-high-definition video rendering unit, so that the audio and video quality is improved, the detail performance of the video picture is enhanced, the user experience is improved, the audio and video transmission synchronization precision is evaluated through the inter-frame delay and the audio delay based on the optimized ultra-high-definition video, and the user experience is improved. And audio and video synchronous transmission is realized.

The invention relates to the technical field of image processing, and discloses a video processing method, device, equipment and medium, and the method comprises the steps: obtaining video data, vehicle speed data, vehicle angular speed data and illumination intensity data from a vehicle-mounted terminal, the resolution of the video data being a first resolution; fusing the video data, the vehicle speed data and the vehicle angular speed data based on the timestamp to obtain fused data, and performing motion compensation based on the fused data to generate intermediate frame data; extracting multi-scale feature data based on the intermediate frame data, the illumination intensity data and the preprocessed data, and generating texture data based on the multi-scale feature data; and performing dynamic weighting based on the intermediate frame data, the multi-scale feature data and the texture data to generate processed video data, the resolution of the processed video data being a second resolution, and the first resolution being lower than the second resolution. The image quality bottleneck of an inherent automobile data recorder of a vehicle can be broken through, and video dynamic optimization is realized.

The present invention relates to the field of video data processing technology, and in particular to a method and system for secure transmission of electronic information privacy data, the method comprising: iteratively segmenting the video data to be transmitted as target video frames in turn, analyzing the grayscale distribution of pixel blocks of the target video frames, the degree of grayscale difference in the neighborhood, and the gradient characteristics of document information distribution, constructing the intra-frame detail segmentation requirement, document segmentation correction coefficient, and document segmentation penalty factor; obtaining the intra-frame document correction segmentation requirement; analyzing the grayscale difference of pixel blocks at the same position of the target video frame and the video frame in the time neighborhood, constructing a grayscale motion index sequence and an inter-frame motion change rate; obtaining dynamic information complexity; and using a long edge conditional segmentation method to achieve adaptive dynamic segmentation of video frames to complete video optimization transmission. The present invention aims to achieve adaptive dynamic segmentation of video frames, retaining details while achieving better transmission effects.

Data encryption and Human Pose Estimation based on imaging a body segment. A key for encrypting a data file is generated based on image data that represent a unique biometric feature of a body segment of a user or motion of the user. An image engine executes artificial intelligence to identify matching image data for decrypting the data file. The image engine is further trained to predict changes in image data due to aging, stress, and the like. An avatar associated with the user, which is generated based on a movement pattern of the user, is configurable for generating an encryption key and for use in an avatar-based language.

The present invention provides a video optimization method, device, equipment and medium in a low-light environment, which belongs to the field of image denoising. The method includes: obtaining motion vectors and continuous frames of a target video in a low-light environment; converting the motion vectors into an optical flow map, further smoothing the optical flow map according to the context information of the image frames in the continuous frames to obtain a rough optical flow map; determining the correlation between two adjacent image frames in the continuous frames; iteratively optimizing the rough optical flow map according to the correlation. In this way, the optical flow map is converted into a rough optical flow map through the context information of the continuous frames of the image, and then the rough optical flow map is used as an initial value for iteration. In this way, corresponding optical flow processing is performed for different videos, which has high versatility, and the optical flow processing can go deep into the pixel level of the target video, which has high robustness. Finally, the iteration of each pixel is realized through the optical flow processing, thereby completing the optimization of the target video.

The present invention relates to an encoding / decoding method and apparatus for using optimized quantization according to a video, a method for transmitting a bitstream, and a bitstream storage medium. A decoding method according to an embodiment of the present disclosure may comprise the steps of: acquiring data optimization information related to a video data optimization method according to a purpose of video data; and reconstructing the video data based on the data optimization information, wherein the data optimization information includes data optimization application information indicating whether to perform optimization on each use of the video data.

The invention discloses an intelligent processing method and system for multi-modal data of an oral broadcast video based on deep learning, and relates to the technical field of oral broadcast video data processing, and the method comprises the following steps: 1, collecting multi-modal oral broadcast data in real time, recognizing emotion types, and carrying out the data preprocessing; step 2, constructing an oral playing animation generation model, judging the synchronization degree of the mouth shape, the head action and the audio in the oral playing animation, and taking coordinated regulation measures; 3, judging the consistency of the mouth shape and the emotion intensity in the oral playing animation, and implementing an anomaly repair measure; 4, constructing a depth time sequence prediction model, evaluating the difference degree between the actual oral playing animation and the prediction result of the depth time sequence prediction model, and carrying out video optimization and model tuning; the problems that when mouth shape supplement and animation filling are carried out by AI, precise synchronization of mouth shapes, expressions, head actions and emotional fluctuations is difficult to achieve, so that visual abnormity is caused, and the reality sense and the professional degree of videos are affected are solved.

The invention relates to the technical field of computer vision, and discloses a night image and video processing system and method suitable for an unmanned aerial vehicle. The method comprises the following steps: establishing an unmanned aerial vehicle night scene image collection module, an unmanned aerial vehicle night scene image preprocessing module, an unmanned aerial vehicle night scene data calculation module, an unmanned aerial vehicle night scene data analysis module and an unmanned aerial vehicle night image and video optimization module, the unmanned aerial vehicle night scene image preprocessing module performs different formatting preprocessing on acquired night scene imaging pictures and videos, and adopts a bilateral filtering image enhancement algorithm formula to suppress noise, and the unmanned aerial vehicle night scene data calculation module is used for calculating data; the unmanned aerial vehicle night scene data analysis module compensates a shadow image of the unmanned aerial vehicle in night flight according to a calculation result, and the unmanned aerial vehicle night image and video optimization module optimizes parameters of an image enhancement algorithm according to an analysis result.

The invention discloses a mine disaster self-rescuer AI video identification practical training system, which belongs to the technical field of coal mine safety simulation, and comprises a shooting simulation module for simulating an underground environment, an operator wearing a mine disaster self-rescuer in the simulated environment, shooting a wearing process and a simulation process, and carrying out real-time video identification on the mine disaster self-rescuer. The video optimization module optimizes the video frame image with poor image quality, and the action analysis module performs key point detection and action recognition on the optimized video to obtain the operation steps of an operator and judge whether the action is completed or not; the multi-dimensional scoring module constructs a quantitative scoring model according to the time dimension, the action specification dimension and the component operation dimension, and scores the operation process of the operator, so that the operator can practice in an environment close to reality, the operation proficiency and psychological quality of the operator in an emergency scene are improved, and the user experience is improved. Emergency operation errors caused by insufficient environment adaptation are avoided, the action judgment accuracy is improved, and a comprehensive and objective quantitative basis is provided for practical training effect evaluation.

The application discloses an audio and video optimization processing method and system for a handheld terminal, and relates to the technical field of multimedia signal processing, which comprises the following steps: independently of an audio coding process, a lightweight neural network model is used to perform real-time analysis on original audio data in parallel, and a structured audio semantic descriptor is output; in response to a selected current video coding strategy mode, a set of operation parameters of a video encoder is dynamically reconstructed to code a synchronously collected video frame; if the current video coding strategy mode is a speech active mode, the coding frame rate is increased and a region of interest coding for a face region is started; if the current video coding strategy mode is a music dominant mode, the coding resolution is increased; and if the current video coding strategy mode is a silent listening mode, the coding frame rate and resolution are reduced. Through dynamic video coding strategy adjustment based on audio semantics, the application realizes accurate balance of video quality, smoothness and resource consumption.

The application discloses a short video optimization method and device based on a knowledge graph, computer equipment and a readable storage medium, and comprises the following steps: firstly, a target short video link and basic information are acquired, and a big data service of a net celebrity is called; then, based on the basic information and a net celebrity knowledge graph, deep information is extracted through a big language model of the net celebrity; finally, the basic information and the deep information are input into the model to obtain optimization suggestions. In this way, various technical resources are cooperated, the value of the short video is effectively mined, and the propagation effect is improved.

The invention discloses a marketing video automatic editing method based on machine learning, relates to the technical field of artificial intelligence video processing, and solves the problems that the marketing video editing efficiency is low and the content is disjointed from user preference. According to the method, video clips are extracted, visual and audio features are analyzed, key emotional climax clips are recognized, a narrative path is constructed by adopting an attention mechanism, a sequence is optimized to generate a personalized video, a transition effect is inserted, parameters are rendered and determined, a complete video is generated, interaction potential is optimized, and automatic intelligent editing is achieved. And the content creation efficiency and the user interaction capability are improved.

The invention provides a fast holographic video optimization method based on a clustering algorithm for solving the problem that the calculation speed of holographic video optimization is low. According to the method, the calculation complexity in holographic video optimization is remarkably reduced by introducing the clustering algorithm. The optimized hologram of the center of the cluster is obtained firstly and serves as the initial hologram of other frames in the cluster, the optimization speed is increased, and the quality of the optimization result is guaranteed. According to the method, while holographic video optimization calculation is accelerated, high reconstruction quality is kept, and the method has a wide application prospect.

The invention relates to the technical field of monitoring, and discloses a monitoring video optimization method based on a transformer substation three-dimensional model, which comprises the steps of data acquisition, three-dimensional model construction, preprocessing, video analysis, abnormity judgment and information display, and is accurate in three-dimensional model construction and effective in application. A model constructed by combining laser scanning and 3DMAX software truly restores a substation scene, and an accurate space basis is provided for video analysis. The marking and displaying functions are highlighted, so that monitoring personnel can visually check abnormity and changes in the three-dimensional model, and the monitoring intuition and effectiveness are improved; abnormality judgment and analysis are scientific and reasonable, the abnormal evaluation value is calculated through comprehensive analysis of multiple video frames, abnormal events are accurately recognized, abnormal information is fed back in time, rapid positioning and processing are assisted, the response and processing efficiency of abnormal conditions of the transformer substation is improved, safe and stable operation of the transformer substation is comprehensively guaranteed, and the method has important practical application value.

The invention discloses a video optimization method and system based on wireless transmission, and belongs to the technical field of image communication. According to the scheme, the self-adaptive bandwidth allocation effect is achieved through signal intensity monitoring, various optimization modes are adopted, the problems of image distortion and untimely operation in wireless transmission can be effectively solved, and the user experience can be remarkably improved especially in the fields of cloud games, telemedicine, unmanned aerial vehicle control and the like with extremely high real-time performance requirements. According to the method, a prediction algorithm is combined, data for decoding can be obtained more quickly through comparison and correction of an actual frame and a predicted frame, and perception loss is relieved by adopting modes of inter-frame interpolation, frame freezing, background filling and the like.

The present invention discloses a CCBT system data processing method based on visual-linguistic multimodal information, and relates to the technical field of depression detection. The CCBT system data processing method based on visual-linguistic multimodal information includes the following steps: data acquisition; audio effectiveness evaluation; video effectiveness evaluation; optimization effectiveness evaluation. The present invention obtains an audio effectiveness evaluation value through the acquired voice features, determines whether to perform audio optimization based on the audio effectiveness evaluation value, then obtains a video effectiveness evaluation value based on the acquired video features, determines whether to perform video optimization based on the video effectiveness evaluation value, and finally obtains an optimization effectiveness evaluation value based on the test data and the test data obtained after the test optimization, determines whether to perform feedback based on the optimization effectiveness evaluation value, thereby improving the accuracy of depression diagnosis data processing in the CCBT system, and solving the problem of low accuracy of depression diagnosis data processing in the CCBT system in the prior art.

The present invention belongs to the technical field of image processing, and particularly relates to a video optimization acquisition method for an intelligent factory area based on machine vision, including: performing Gaussian mixture background modeling on the production line area in the surveillance video, and dividing pixel points into several first categories according to the distances between the Gaussian mixture models of different pixel points; constructing a sub-Gaussian serial number sequence for each pixel point, and dividing the pixel points in the first category into several second categories according to the differences between the sub-Gaussian serial number sequences of the pixel points in the first category; determining the possible abnormal degree of each pixel point in the current video frame according to the dislocation differences between the sub-Gaussian serial number sequences of the pixel points in the second category; and adjusting the acquisition frequency level of the surveillance video according to the magnitudes of the possible abnormal degrees of each pixel point. The present invention dynamically adjusts the sampling frequency level, achieving a balance between monitoring accuracy and system efficiency.

The invention relates to the technical field of image data processing, in particular to a community video optimized acquisition method based on artificial intelligence, which comprises the following steps: acquiring each video frame of a community video, and dividing any video frame into a plurality of target areas; performing noise removal processing on each video frame by using an improved Gaussian filtering algorithm so as to obtain each video frame after noise removal; and reconstructing a community video based on each video frame after noise removal. Wherein the improved Gaussian filtering algorithm comprises a weight value, and the weight value is related to a noise parameter of the target area and a mean value of gradient amplitudes of all pixel points in the target area. The problem that edge information is lost or noise remains when an existing Gaussian filtering algorithm is used for noise removal processing is solved.

The invention discloses a video optimization method and device for a set top box, a medium and equipment, relates to the technical field of video processing, and aims to solve the problem that in the prior art, audio and picture synchronization means for videos can cause reduction of user experience. According to the method and the device, when the watching effect becomes poor due to audio and picture asynchronization when the user watches the video, the user autonomously initiates the synchronization instruction, the live video after the instruction is initiated is cached, and then the cached data is played to replace the live video, so that the watching integrity of the user is ensured, and the user experience is improved. In the process of playing the cached video, the lagging one of the picture and the audio is enabled to accelerate the playing rate, the audio and the picture are enabled to be gradually synchronized under the conditions of no interruption and clamping stagnation, and the time point during synchronization is taken as a mark to switch back to the live video, so that the currently played picture of the live video is enabled to be synchronized with the timestamp of the audio, and the playing speed is improved. The audio and picture synchronization of the set top box video is realized, and the watching experience of the user is effectively enhanced.

The application discloses a real-time high-speed target recognition and tracking scheme based on a domestic artificial intelligence framework, realizes rapid target detection and accurate tracking by combining target recognition and tracking technology, can automatically restart the recognition network and reposition when the system loses the target, supports manual selection of target tracking by the user, adopts a self-developed long-time tracking algorithm, is not limited by the target category, processes multiple videos in the front end, optimizes the use of computing resources, and improves the processing speed and efficiency by optimizing the hardware visual preprocessing and network inference part. The system provides a flexible output mode and is suitable for various application scenarios.

The present invention relates to a system (1) for customizing video contents for specific target audiences or individuals through artificial intelligence.

The present invention provides a method for generating a comic video based on domain adaptation, comprising the following steps: first, use a face video dataset to train a motion-driven network; for a given source image and a driving frame input to the pre-trained motion-driven network, it can generate and output a target video of the given source image according to the motion of the driving frame; then, use the face video dataset and the comic dataset to train a cross-domain network; introduce a domain discriminator, and use a gradient reversal layer to confuse the face video dataset and the comic dataset to maximize the domain classification error. The present invention first uses a face video dataset to train for the image dynamicization task, and then adapts it to the comic domain using the domain adaptation method, solving the problems of overfitting and poor generalization ability that are likely to occur when directly using the small number of comic datasets for training, and does not require per-video optimization, ensuring the quality and stability of the generated video.