2457 results about "Video processing" patented technology

An example operation may include at least one of receiving, via a user interface of a device, an activation input from a user to initiate a session, capturing, by a camera of the device, a scan of a body of the user, wherein the capturing comprises recording at least one image and / or at least one video of the user, processing the at least one image and / or video to generate a three- dimensional model of the user comprising measurements and contours of the body, retrieving, from a database, at least one clothing item associated with the user, the at least one clothing item comprising dimensional attributes and texture attributes, rendering, by a graphics processing unit, the at least one clothing item onto the three-dimensional model to generate a visual representation, wherein the rendering simulates draping behavior, movement, and light interaction of the at least one clothing item relative to the three-dimensional model, and displaying, on the user interface, an interactive visualization comprising the visual representation of the three-dimensional model with the at least one clothing item from multiple viewing angles.

The invention relates to the technical field of computer video processing, and discloses a low-delay video stream real-time processing method and device, and the method comprises the steps: obtaining original video stream data, and processing the original video stream data through employing a lightweight motion prediction method; processing the macro block data set and the predicted coding configuration parameter by adopting multi-thread assembly line coding to obtain a coded data block; establishing a data transmission mechanism to perform data flow control on the unified memory access interface; a heterogeneous task scheduling strategy is adopted to distribute task division results; a lightweight neural network is adopted to carry out parameter adaptive adjustment, and an optimized video stream processing result is obtained; according to the method, a zero-copy data transmission technology is adopted, and optimal configuration and efficient utilization of computing resources are achieved.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. In the method, for a conversion between a current video block of a video and a bitstream of the video, a process is applied to the current video block based on template matching. At least one reference sample of a current template of the current video block is determined based on a block vector (BV) of the current video block during the process. The conversion is performed based on the applying.

The embodiment of the invention provides a model training method, a facial expression recognition method and device and electronic equipment, and relates to the technical field of video processing. The model training method comprises the following steps: acquiring a sample video and a first sample label; extracting a time feature and a space feature of the sample video by using a time-space feature extraction network in the facial expression recognition model of the initial structure; calculating an attention weight representing the correlation between the spatial feature and the time feature by using a mapping network; performing weighted aggregation on the time features by using the attention weight to obtain fused spatio-temporal features; inputting the fused spatial-temporal features into a classification network to obtain a first recognition result; and performing model training based on the difference between the first recognition result and the first sample label to obtain a trained facial expression recognition model with higher accuracy.

The invention provides a facial skin flaw enhancement method based on a Lab color space. The method comprises the following steps: firstly, acquiring an RGB face image and converting the RGB face image into a CIE Lab color space with uniform perception; then, performing differentiation treatment according to the manually selected skin flaw type: for the vascular flaw, extracting statistical characteristics of a component and driving adaptive nonlinear transformation, and generating a grey-scale map which highlights the red flaw; for pigment flaws, nonlinear transformation is carried out on the component L, and then collaborative linear weighting and feature amplification are carried out on the component L, the component a and the component b, so that a grey-scale map with highlighted pigment spots is generated. And finally, coloring the grey-scale map in the Lab color space through adjustable parameters to generate a high-contrast color enhanced image. The method overcomes the dependence on hardware and training data in the prior art, can clearly and adaptively enhance various flaws such as acnes, couperose streaks and color spots, shows robustness under different illumination, and can be widely applied to clinical beauty, later photography and real-time video processing.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: obtaining, for a conversion between a current video block of a video and a bitstream of the video, first information regarding whether to filter a prediction for a chroma component of the current video block, wherein the prediction for the chroma component is determined with a cross-component prediction (CCP) mode, and the first information is dependent on coding information associated with the current video block; and performing the conversion based on the first information.

The invention relates to a risk prediction and emergency navigation system based on digital twin and AI video linkage, and belongs to the technical field of public safety and emergency management. The system comprises an AI video processing module, a digital twin module, a risk prediction module and an emergency navigation module, analyzing the target area video data stream, and extracting target dynamic behavior features to generate video feature data; the digital twinborn module fuses the real-time environment parameters and the video feature data, constructs and updates a video linkage twinborn model, and outputs spatial state data; the risk prediction module is combined with a space-time fusion prediction mechanism and a historical risk case library to calculate a risk occurrence probability, a risk level, an influence range and an evolution trend; and the emergency navigation module dynamically plans a path and generates navigation information adaptive to different users and terminals based on the risk prediction result and the spatial state data. According to the method, deep fusion of multi-source data is realized, the risk prediction accuracy and navigation dynamic adaptability are improved, and the method is suitable for various scenes.

The invention relates to the technical field of audio and video processing, and provides an intelligent card pause prevention optimization method and system for audio and video playing. According to the method, firstly, a playing state data set is collected in real time, and the playing state data set comprises code stream parameters, hardware resource occupation data and network transmission state parameters; then, constructing a play load association graph based on the data set, and describing a mutual influence relationship among parameters; then, generating a dynamic resource allocation strategy according to the play load association map, and adjusting a hardware resource allocation proportion and a network transmission priority; and finally, executing the strategy, continuously monitoring the data change, and dynamically adjusting the strategy to maintain the playing fluency. Therefore, through multi-parameter correlation modeling and dynamic optimization, accurate prevention of lagging is realized, and the audio and video playing experience is improved.

The invention relates to the technical field of audio and video processing, in particular to an unmanned live broadcast management system based on a video streaming technology. The system comprises a data acquisition module used for synchronously acquiring multi-modal real-time data streams including videos and audios from multiple dimensions; the real-time analysis module is used for analyzing the competition and outputting structured data including key events and competition narrative states; the automatic narrative director module is used for generating a director instruction based on the narrative logic model, and controlling shot selection, image-text generation and automatic explanation; the manufacturing and distributing module is used for synthesizing and distributing the final program stream at low delay; and the management module is used for configuring, monitoring, scheduling and managing the live broadcast process. Through multi-modal fusion analysis and narrative logic driving, automation and intelligentization of the whole process from data acquisition to content distribution are realized, the ornamental value, accuracy and management efficiency of unmanned live broadcast are remarkably improved, and meanwhile, the manufacturing cost is reduced.

The invention relates to the technical field of video processing, in particular to a multi-video semantic collaborative analysis method and system based on federated learning. Obtaining task complexity reported by the plurality of end-side computing devices respectively; dividing the plurality of end-side computing devices into K device groups based on the plurality of task complexities; respectively initializing K semantic analysis models for the K equipment groups at a server side; based on a federated learning framework, cooperating with a plurality of end-side computing devices and a server side to carry out layered distillation training on the K semantic analysis models; and correspondingly issuing the trained K semantic analysis models to each end-side computing device in the K device groups for video semantic analysis. According to the method, the overall efficiency, accuracy and generalization ability of multi-video semantic collaborative analysis can be improved, and configuration of computing resources is optimized.

This disclosure provides an AI filmmaking workflow including AI-assisted storyboarding, AI animation, and post-production processes for creating films. The workflow provides techniques for reconstructing 3D digital environments and characters, and for virtual camera control. The workflow also provides techniques for capturing 2D live-action performances and extracting visual cues. The AI animation process generates synthetic images and video using prompts that are based on virtual camera control in case of 3D digitization and / or visual cues in case of 2D camera capturing. Further, the workflow provides techniques for compositing with AI assistance, to generate a composited video based on the AI-animated video and inputs resulting from 3D digitization and / or 2D video processing. Advanced post-processing techniques are also provided for generating a complete film based on the composited video. This framework is designed to facilitate creative collaborative networks by using a hybrid digitization approach to enhance consistency, directability, and scalability in AI filmmaking.

The embodiment of the invention provides a video processor, a video processing method, video processing equipment, a storage medium and a program product. In the scheme, after the display layer receives the special effect style configuration, the algorithm engine layer calls the matched physical mathematical model according to the target special effect style and the basic video, outputs the high-fidelity special effect description file, and improves the special effect parameter accuracy; the rendering adaptation layer dynamically selects an optimal rendering engine according to the resources of all the rendering engines, and the time consumption of single-example rendering is shortened; two-layer hierarchical decoupling is adopted, so that description file generation and rendering execution are parallel, batch description files can be shared by multiple preview positions after being prepared at one time, rendering resources are only input when real preview requirements are met, and idling is avoided; the display layer, the algorithm engine layer, the rendering adaptation layer and the rendering layer are sequentially relayed to form a compact link of quasi-generation-fast rendering-playback, so that waiting and repeated export links of a user in a subsequent video editing stage are remarkably reduced, and the video editing efficiency is integrally improved.

The invention relates to the technical field of endoscope video processing and intelligent edge computing, in particular to an endoscope video enhancement processing intelligent edge computing system. Comprising a data acquisition module which is used for acquiring an original video frame sequence of edge endoscope equipment in real time; the feature extraction module is used for determining an instantaneous feature vector representing the dynamic change of the operation scene; the criticality quantification module is used for quantizing and generating a surgical event criticality score; the tuning logic module is used for generating a discrete and stable calculation normal form switching instruction; the assembly line switching module is used for responding to the calculation normal form switching instruction and executing an asynchronous weight preheating strategy; the utility evaluation module is used for constructing a dynamic utility function to evaluate system performance; and the threshold value correction module is used for performing closed-loop correction on the high-criticality threshold value by adopting a gradient rising strategy. According to the method, the stability of system decision making is enhanced, the smooth transition of the video processing flow among different calculation paradigms is ensured, and the robustness of the system is improved.

The invention discloses a light-weight few-sample man-machine interaction action recognition method, system and equipment, and belongs to the technical field of video processing and computer vision. The problems that an existing method is large in parameter quantity, high in computing resource requirement and difficult to meet the real-time performance are solved, the spatial-temporal features of the action fragments are extracted through the lightweight deep neural network, dynamic and scene information is fused, the classification model is optimized by combining sliding collection and the cycle completion technology, low-time-delay and high-robustness action recognition is achieved, and the real-time performance is improved. The method is suitable for real-time monitoring of industrial processes, does not need a large amount of labeled data, and reduces the calculation complexity. By analyzing the difference between action transition and normal action and utilizing a Gaussian mixture model and Bayesian optimization to dynamically adjust a threshold value, the accuracy and robustness of action recognition are improved, high-quality data support is provided for model training and action recognition, and the automation level of action segmentation is remarkably improved.

The method is mainly applied to the technical field of artificial intelligence processing. The invention discloses a face and license plate privacy protection video processing method, device, equipment and medium, and the method comprises the steps: extracting input video data to obtain a video frame sequence which comprises a plurality of video frames; the video frame sequence is input to a pre-trained face and license plate detection model for target detection, so that a target video frame containing a target image area is determined, position information of the target image area in the target video frame is obtained, and the target image area is a face area or a license plate area; based on the position information of the target image area, performing fuzzy processing on the target image area in each target video frame; and generating a video after fuzzy processing based on the video frame after fuzzy processing. According to the method and the device, the privacy protection and the target detection are collaboratively optimized, so that the efficiency and the accuracy of target detection are improved while the privacy security is guaranteed.

The invention provides a video processing method, a video processing device, electronic equipment and a computer readable storage medium, and belongs to the technical field of data processing. The method comprises the following steps: acquiring a to-be-processed video stream, and identifying the to-be-processed video stream to determine static frame data in the to-be-processed video stream; generating semantic prompt information according to the static frame data; performing video frame optimization on the to-be-processed video stream according to the static frame data to obtain an optimized video stream; and processing the semantic prompt information and the optimized video stream by adopting a target language model to obtain a processing result. The model reasoning efficiency can be improved.

The present disclosure relates to methods and apparatuses for decoding data for (still or video processing into a bitstream). Two or more sets of segmentation information elements are obtained from the bitstream. Then, each of the two or more sets of segmentation information elements are inputted respectively into two or more segmentation information processing layers out of a plurality of cascaded layers. In each of the two or more segmentation information processing layers, the respective sets of segmentation information are processed. The decoded data for picture or video processing are obtained based on the segmentation information processed by the plurality of cascaded layers. Accordingly, the data may be decoded from the bitstream in an efficient manner in the layered structure.

An active receiver card for a display is provided. The active receiver comprises a processor, a first interface, and a second interface. The first interface is configured to receive a broadcast serialized video data stream as input from a video processing system. The active receiver card is configured to be electrically connected to a tile of a display. The active receiver card further comprises a second interface configured to output control signals to a plurality of pixels of the tile of the display. The processor of the active receiver card is configured to extract from the received broadcast serialized video data stream video image data pertaining to the tile of the display, and based thereon, the active receiver card is configured to output the control signals used to control a plurality of pixels of the tile of the display.

The invention discloses a time-space consistency-based video super-resolution method and device for a complex operation scene, and a medium, belongs to the field of image and video processing, and aims at solving the problem that a stable, clear and continuous-structure video sequence is difficult to generate in an existing method, and the time-space consistency-based video super-resolution method for the complex operation scene based on video prior is provided. Comprising the following steps: utilizing submerged space modeling, mapping an input low-resolution video to a submerged space, and obtaining a corresponding submerged variable representation; initializing a random noise tensor with the same size as the latent variable expression as an initial noise state; in each step of sampling, dividing a noise state and latent variable representation into a plurality of blocks according to space and time dimensions; denoising is carried out on each tile block; the initial noise is converted into high-quality latent variable representation; and a high-resolution video is reconstructed. According to the method, the power inspection video with high resolution and high consistency can be generated, the generation stability is kept, and the video texture detail expression capability is improved.

The invention relates to the technical field of computer vision and video processing, and discloses a cross-domain multi-target automatic detection tracking association method based on an unmanned aerial vehicle platform, which comprises the following steps: firstly, obtaining an effective detection frame of a current frame through a target detector; meanwhile, a tracking bounding box is obtained through a tracker and a self-adaptive time sequence converter; then, executing three-level progressive data association: executing the first-level data association based on space association, and rapidly associating a target with continuous motion; the second stage performs re-recognition association on unassociated targets to process occlusion and reproduction; in the third stage, new track initialization is executed after multi-frame verification and quality evaluation are carried out on the detection frames which are still not associated; and finally, executing track life cycle management, and performing updating, state change or deletion on all tracks. According to the invention, through sequential context modeling and progressive fusion of depth features, the tracking precision, robustness and target identity retention capability in complex scenes (such as unmanned aerial vehicle maneuvering) are improved.

The invention relates to the technical field of monitoring video processing, and discloses a coal mine shaft fault monitoring method and system. Comprising the steps of collecting video streams of key positions in a coal mine shaft in real time; splicing the original image frames in the video stream of each key position according to a space-time relationship to obtain a panoramic monitoring picture at each moment; segmenting the panoramic monitoring picture at each moment according to the target monitoring object to obtain a segmented image frame corresponding to each target monitoring object; performing fault analysis on the segmented image frames corresponding to the target monitoring objects to obtain monitoring results of the target monitoring objects; and obtaining a monitoring result of the coal mine shaft based on the monitoring results of all the target monitoring objects. The comprehensive monitoring result of the whole coal mine shaft can be automatically generated, intelligent, precise and efficient monitoring of underground potential safety hazards is achieved, and the safety of the monitoring process can be remarkably improved.

The invention discloses an unmanned aerial vehicle target tracking method based on motion perception and feature enhancement, and relates to the technical field of unmanned aerial vehicle video processing. In order to enhance the response capability of a tracking network to a dynamic target and improve the robustness in a motion sudden change scene, a Transform architecture is adopted to extract global features, and a motion sensing module is introduced to perform modeling on target motion. A smooth deformation field is generated through a sparse offset prediction module to realize motion compensation, and the compensation precision is further improved by using a motion decoupling module. In addition, an adaptive motion attention enhancement module is designed, and the module adaptively adjusts the attention intensity according to the motion information. And finally, predicting a target bounding box by the classification regression network. According to the method, the feature expression is enhanced by effectively utilizing the motion information, and the tracking accuracy is remarkably improved.

Embodiments of the disclosure provide a solution for video processing. A method for video processing is proposed. The method includes: obtaining, for a conversion between a target frame of a point cloud sequence and a bitstream of the point cloud sequence, a predicted value of the target frame by performing at least one of: alternating current (AC) prediction or direct current (DC) prediction in a domain; and performing the conversion based on the predicted value.

A method of video processing is provided. The method may include inputting attribute data and a sparse-depth map associated with an image area into a sparse-depth completion network. The method may include generating a refined dense-depth map based on the attribute data and the sparse-depth map using the sparse-depth completion network. The method may include performing a three-dimensional (3D) reconstruction procedure based on the refined dense-depth map to generate a point cloud of the image area. The method may include performing a triangular-meshing procedure to generate a mesh model based on the point cloud of the image area. The method may include performing a texture-mapping procedure based on the mesh model and the attribute data to generate a textured mesh of the image area. The method may include performing a vertex-normal procedure based on the textured mesh to generate a 3D representation of the image area.

Embodiments of the disclosure provide a solution for video processing. A method for video processing is proposed. The method includes: determining, for a conversion between a video unit of a video and a bitstream of the video, motion information of the video unit based on template matching for intra block copy (IBC) or intra template matching prediction (IntraTMP), wherein the template matching for IBC or IntraTMP is different from template matching for inter prediction; and performing the conversion based on the prediction or reconstruction of the video unit.

The invention provides a video processing method and device and electronic equipment, and the method comprises the steps: inputting a target video into a coding model, and determining the potential spatial features of each video frame through the coding model; constructing a similarity kernel matrix based on the potential spatial features; determining candidate sub-matrixes from the similarity kernel matrix, and determining the candidate sub-matrix with the maximum element difference among matrix elements in the candidate sub-matrixes as a target sub-matrix; and carrying out dimension reduction processing on the target sub-matrix, and outputting compressed data of the target video based on a dimension reduction result through a decoding model. In the mode, based on the potential spatial features of the target video determined by the encoder, the similar kernel matrix is constructed, representative samples are selected from the similar kernel matrix, dimension reduction is carried out on the samples, and the dimension reduction result is reconstructed again through the decoder, so that more redundant information can be removed on the premise of retaining data information, and the accuracy of the data information is improved. And data processing is performed in the potential space, so that the calculation cost is reduced, and the requirements of reducing storage and calculation resources are met.

Embodiments of the disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: performing, for a conversion between a video unit of a video and a bitstream of the video, a refinement on a prediction or reconstruction of the video unit by applying a filter for the video unit; and performing the conversion based on the refined prediction or refined reconstruction.

The invention discloses a video synthesis method and system, and relates to the technical field of audio and video processing. A video synthesis system comprises a video source acquisition and processing module, a cross-modal semantic understanding module, an attention tensor generation module, a hierarchical progressive fusion module and a quality evaluation and optimization module. According to the method, the spatial-temporal joint features are extracted through the three-dimensional convolutional network, and the audio-visual cross-modal attention mechanism is constructed, so that the dynamic association strength of the audio event and the video content can be quantified, and the main body space mask can be generated, and therefore, the traditional isolated visual processing can be expanded into sound and picture semantic linkage understanding; in this way, deep guidance of multi-modal information on the synthesis process is achieved, and the synthesis effect of the video synthesis method and system is improved.

Embodiments of the disclosure provide a solution for video processing. A method for video processing is proposed, and includes: deriving, during a conversion between a target block of a video and a bitstream of the vide, an intra prediction mode (IPM) of the target block for at least one chroma component, the target block being applied with a target coding tool; obtaining a prediction of the target block for the at least one chroma component using the IPM, wherein during a derivation of the IPM for the at least one chroma component, an intra prediction is processed on a first template using one of IPMs from a first IPM candidate list, and a candidate IPM with a minimum cost is derived as the IPM for the at least one chroma component; and performing the conversion based on the prediction of the target block for the at least one chroma component.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: obtaining, for a conversion between a current video unit of a video and a bitstream of the video, first information regarding whether to enable a coding scheme for the current video unit, the first information being determined based on at least one of the following: a video content type of the current video unit, a type of a boundary of the current video unit, gradient information associated with the current video unit, or coding mode information of a neighboring video unit of the current video unit; and performing the conversion based on the first information.