625 results about "Video output" patented technology

A video output device includes a projector module configured to output a content image along a radiation direction, a first rotating device configured to rotate at least a portion of the projector module about a first axis that is parallel to the radiation direction, a second rotating device configured to rotate the projector module about a second axis intersecting the first axis, a substrate electrically connected to the second rotating device, and a connector electrically connected to the substrate through a first wire, electrically connected to the second rotating device through a second wire. While the projector module rotates about the second axis, the connector is configured to prevent the first wire and the second wire from being twisted.

The invention provides a multi-screen cabin entertainment system, and relates to the technical field of embedded systems and intelligent cabins, and the multi-screen cabin entertainment system is characterized in that an application layer is deployed with a plurality of cabin entertainment applications, and when the application layer is started, content rendering requests are sent out respectively; the hardware layer is provided with a development board, is provided with a CPU core cluster and a coprocessor, and is connected with different cabin display screens through different video output interfaces. The system layer respectively distributes an independent thread and an independent frame buffer area for each content rendering request on the CPU core cluster, and establishes a mapping relation between each frame buffer area and each video output interface; and sending operation result data of each independent thread to a coprocessor for rendering, correspondingly storing a rendering result in a frame buffer area, and then sending the rendering result to a cabin display screen for display through a video output interface. The method has the advantages that on the premise that the number of hardware coprocessors is not increased, complete separation of multi-screen rendering threads and frame buffer is achieved, and multiple cockpit entertainment applications can run at the same time and do not interfere with one another.

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 discloses a virtual fitting video generation method and system based on multi-view face fixation, and relates to the field of generative artificial intelligence and computer vision, and the virtual fitting video generation method based on explicit geometric constraints comprises the following steps: S1, obtaining an original fitting image and an action cue word, and constructing a multi-source input data set; s2, segmenting the original fitting image to obtain multi-view modeling, and generating a multi-angle face image and a clothing texture feature parameter; s3, analyzing the action cue word to generate a target posture sequence, and generating head and tail frame virtual fitting images; s4, performing pairing analysis on the virtual fitting images of the head frame and the tail frame to generate attitude transition parameters; s5, performing dynamic texture repair on the image to generate a transition frame image sequence; and S6, generating a virtual fitting video and outputting the virtual fitting video. According to the method, accurate segmentation and multi-angle modeling of the face area and the clothing area are realized through image segmentation and a rigid geometric transformation algorithm.

Provided in the present invention is a video stabilization method that deeply integrates optical flow and IMU data. The method comprises: acquiring and preprocessing data, computing optical flow, computing historical data of an original pose and a stable pose, predicting a stable camera pose, implementing video stabilization, and training a deep learning model, wherein computing the optical flow involves mixing the optical flow and translation of a camera between adjacent frames as parameters of a translational motion of the camera and inputting the parameters into a deep learning network; computing the historical data of the original pose and the stable pose and predicting the stable camera pose involve using an LSTM network to train and predict stabilization quaternion; and implementing video stabilization involves dividing a video frame into rectangular grids, transforming vertices of the grids by means of the quaternion output by the deep learning network, obtaining each pixel value in the video frame by means of performing quadratic interpolation on four vertices of the grid where the pixel value is located, and processing each pixel value to obtain a stabilized video frame. The method of the present invention can adapt to complex motion scenarios and provide a highly stable video output.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a video output using an autoregressive token generation neural network model In one aspect, a system comprises obtaining a model input, processing the model input to generate an input sequence of embeddings that represents the model input, autoregressively generating a plurality of output sequences of tokens, wherein each output sequence of tokens corresponds to a respective output modality of tokens from a set of a plurality of modalities that includes a video modality and one or more other modalities, and generating a model output that includes a video output of the video modality by decoding the sequence of tokens.

The invention discloses a multi-camera collaborative single-target tracking method and device, belongs to the technical field of computer vision target tracking, and is suitable for scenes such as intelligent monitoring and public safety. The method comprises the following steps: constructing a camera space matrix and defining a view field range; the recognition robustness is improved by fusing the target face and the body features; tracking and constructing a target trajectory based on the fusion features; a missing frame is reconstructed or a future frame is predicted through a forward diffusion-reverse generation model, and trajectory coherence is optimized in combination with space-time constraints; probability graph loss optimization of a fixation point area is realized by using an encoder and a saliency prediction module, and finally a video conforming to fixation point constraints is jointly generated. The device comprises a video frame acquisition and preprocessing module, a feature extraction and fusion module, a target tracking module, a missing frame reconstruction and future frame prediction module, a fixation point positioning module, a joint optimization module and a video output module, and all the modules cooperatively realize end-to-end tracking. According to the method, the shielding scene recognition capability is enhanced through multi-modal feature fusion, the problem of track breakage is solved by means of a diffusion model, the monitoring requirement of a specific area is met in combination with fixation point optimization, the precision, continuity and practicability of target tracking in a multi-camera environment are effectively improved, and the method has remarkable technical advantages and application value.

The invention provides an adaptive contrast enhancement video fusion algorithm for a complex logistics scene, and the algorithm comprises the steps: extracting environment features from an initial video data set, analyzing the inter-frame illumination change and object movement speed through employing a convolutional neural network, determining that the current scene is a peak period or a low-illumination environment, and obtaining environment change perception parameters; extracting a key frame from the second video data set, separating a foreground object and a background by adopting an image segmentation technology based on deep learning, and performing detail retention enhancement on the foreground object to obtain a third video data set; real-time verification is carried out on the final video output, if the processing delay exceeds a preset threshold value, the resource distribution proportion is adjusted through a feedback mechanism, mode switching and enhancement processing are executed again, and the updated video output is obtained.

The invention discloses an AI video output system and method combined with a text image model, and relates to the technical field of AI video output, and the system comprises a visual angle conversion and multi-visual angle generation module which comprises a visual angle encoder and a multi-visual angle generator based on semantic-style hidden representation and visual angle vectors, the method is used for generating a multi-angle illustration sequence aiming at different camera parameters and keeping structure and style consistency among different visual angles through time domain consistency constraint in the generation process. According to the method, the artistic style is propagated and maintained among multiple frames and multiple visual angles according to a three-dimensional visual angle transformation rule through visual angle perception style propagation, and the generator outputs a consistent multi-angle illustration sequence under the constraint of a visual angle condition during sampling, so that the problem of inconsistent style drift and deformation under multiple visual angles or multiple lenses is solved; the incoherence of stroke, texture and main body structure caused by visual angle change is avoided, the later manual correction is obviously reduced, and the content consistency and the impression professional degree are improved.

The invention provides a camera quality centralized diagnosis method and system. The method comprises the following steps: regularly obtaining video frames or video streams of a transformer substation camera; determining a quality state of the camera based on the video frame or the video stream; the method specifically comprises the following steps: analyzing the video frame or the video stream, and diagnosing the quality state of the camera according to the quality state of the video frame or the video stream; and if the quality state of the camera is abnormal, triggering an alarm. According to the method, additional equipment is not needed, the state of the camera body is effectively diagnosed by processing and analyzing the pictures or videos output by the camera and combining related judgment rules, the abnormal state of the camera can be found in time, related personnel can be notified, the working reliability and stability of the camera are guaranteed, and the working efficiency is improved. The method can be widely applied to the fields of security monitoring and the like.

The invention discloses a multi-mode-based short episode video editing method, system and device and a medium, and the method comprises the steps: carrying out the preprocessing of an original short episode video, and obtaining a second short episode video, subtitles and a subtitle timestamp; analyzing the subtitles, and generating a short episode abstract according to an analysis result of the subtitles; according to the short episode abstract and the highlight editing prompt, performing plot analysis and editing on the second short episode video, and performing editing to form a first video set; scoring videos in the first video set according to a multi-dimensional scoring rule, and screening out M highlight video clips before scoring; and adjusting the timestamps of the M highlight video clips according to the subtitle timestamps, and outputting the adjusted M highlight video clips. According to the method and the device, the full link from short video input to short play mixed video output is constructed, a user only needs to input the to-be-edited short play video, the mixed video can be automatically generated, and the video editing efficiency is improved while the video editing threshold is reduced.

According to the video stream image optimization method and device provided by the embodiment of the invention, a dynamic fuzzy kernel generation mechanism is innovatively designed, and the data processing security is ensured through space-time decoupling and physical constraint. A content-motion double-branch network is constructed, and a reliable feature reconstruction system is established in combination with residual connection and space-time transformation. A physical constraint corrector is introduced, and high-quality video output is provided while user privacy is protected through adaptive fusion and rule correction. According to the method, the defects of the traditional technology in the aspects of fuzzy processing, feature decoupling, image optimization and the like are effectively overcome.

An image capturing apparatus includes an imaging device configured to capture an image of a subject, a video output unit configured to output a video signal output from the imaging unit, and a metadata output unit configured to output metadata including information related to the video signal, the metadata output unit being different from the video output unit. The video output unit adds information that can identify an individual of the image capturing apparatus to the video signal and outputs the video signal.

[Problem] To provide a video output system, a video output program, and a video output method which are capable of supporting determination of a referee in a match competition and improving the reliability of the determination result. [Solution] Video capturing devices 10 captures a competing scene of both players who compete in a stadium, and the captured videos are outputted to monitors 80 disposed at referees. The output videos are output such that a real-time video is output to a first referee at a constant speed, and a specific video edited by using a part of the real-time video is output to a second referee at a slower speed than the constant speed. On the basis of the specific video, the second referee can verify the determination made by the first referee, thereby improving the reliability of the determination result.

The invention discloses a distributed multi-screen synchronization method, and relates to the technical field of video synchronous display, and the method comprises the steps: forming an output node cluster by a plurality of devices, dynamically electing a main node in the output node cluster, and enabling the main node to serve as a global synchronization controller; the interrupt time sequence of the distributed nodes is synchronized, and alignment of frame taking moments of a video output module VO of the equipment is achieved; and a frame synchronization controller is selected from the distributed nodes, the frame synchronization controller collects the data of the distributed nodes and carries out frame synchronization control, so that multiple devices can synchronously display the same frame of data. Based on a dynamic main node election mechanism, decentralized distributed deployment is achieved, and distributed deployment can be achieved without intervention of an upper computer or input node equipment; by constructing a frame synchronization mechanism based on a global time reference, the tearing and dislocation phenomena of a moving picture are effectively eliminated; and realizing multi-screen synchronization in a sub-millisecond error range through an interrupt synchronization mechanism.

The invention provides a portrait animation generation method, device and system based on audio driving and a medium. The method comprises the following steps: acquiring a figure picture and animation voice data; inputting the character picture and the animation voice data into an animation generation model to obtain a portrait animation video output by the animation generation model; wherein the animation generation model is obtained by training according to a character picture sample and a motion label and a video sample corresponding to the character picture sample; and the animation generation model is used for extracting picture features according to an input figure picture, extracting audio features according to input animation voice data, performing stream matching in combination with an emotion tag predicted based on the audio features, predicting a corresponding video frame based on a potential feature sequence obtained based on a stream matching result, and obtaining a portrait animation video. According to the method, the video can be quickly generated, and natural emotion expression, consistent time sequence and stable generation of the video are ensured.

Systems and methods are disclosed related to a 3D grounded video foundation model. A video generation method and system provide 3D conditioning information to a video diffusion model to improve generated video quality (object and temporal consistency) that is grounded in three dimensions (3D). The video generation method and system also enable precise camera control, cinematic effects, and scene editing. Video output corresponding to a set of camera specifications is generated for a scene from input image(s) including one or more images of a static scene or a sequence of images (video) for a dynamic scene. The input image(s) are used to calculate a 3D cache representing the scene. The 3D cache is rendered according to the set of camera specifications to produce a frame sequence and a mask sequence that identifies missing pixels in each frame. The frame sequence is encoded and masked to generate the output video.

The invention belongs to the field of image processing, and provides a digital human live video synthesis method and system, and the method comprises the steps: receiving the multi-modal data input of a user, and the multi-modal data comprises voice, text and image; key features are extracted from the multi-modal data; fusing the key features to form a fusion condition; generating a corresponding radiation field representation according to the fusion condition by using a neural network model; finely adjusting the radiation field parameters according to real-time input; and converting the generated radiation field into video output.

The invention relates to the field of image processing, and discloses an infrared light shadow interaction system and method. The system comprises an image input device, an interaction main platform, an infrared interaction device and a video output device, wherein the image input device is used for acquiring a contour image drawn by a user; the interaction main platform is used for preprocessing the contour image to obtain a mask combination image, and then performing layer synthesis on the mask combination image and a preset static ancient painting material to obtain a multi-layer image; the infrared interaction equipment is used for capturing a laser point track of a user operation point; and the video output equipment is used for displaying the multi-layer image and binding the coordinate information of the laser points with the coordinate position of the mask combination image so as to control the position of the mask combination image in the multi-layer image based on the coordinate information of the laser points. According to the application, an interaction system with user input, intelligent processing and dynamic display feedback is constructed, and a whole-process closed loop from user creation, image processing and immersive interaction is realized.

The invention relates to the technical field of image stitching, and discloses a video transmission high-definition image intelligent stitching method and system. The system comprises an image preprocessing module, a feature point matching and screening module, an image optimal splicing seam generation module and a video output module. The method comprises the following steps: firstly, acquiring a video, carrying out dynamic range equalization, carrying out filtering processing by using an adaptive noise reduction method, and carrying out image correction; secondly, extracting feature points by using a self-adaptive corner detection algorithm, matching the feature points based on a multi-dimensional spatial data index to obtain feature point matching pairs, and screening the feature points; searching an overlapping region, and introducing a dynamic search algorithm to generate an optimal image splicing path to obtain an optimal image splicing seam; and finally, dividing the image according to the dynamic grid, and realizing video output by using priority ranking. According to the method, the video images are processed and spliced, the purpose of intelligent image splicing is achieved, and the method is accurate and objective.

The invention discloses a video face changing consistency enhancement method based on multi-source feature collaboration, which belongs to the technical field of video processing, and comprises the following steps: S1, video input: inputting an original video, and extracting a frame of image; s2, constructing an expression network; s3, face network construction: extracting face 2D key point picture information, and injecting the face 2D key point picture information into a face network; s4, background network construction: extracting face background information of the video, and injecting the face background information into a background network; s5, constructing an illumination network; s6, feature fusion: splicing outputs of the expression network, the face network, the background network and the illumination network together, and entering a feature extraction network; and S7, video output: injecting the picture information of the reference face and the features extracted by the four networks into a video generation large model, and generating a face changing video by adopting the video generation large model and inputting the face changing video. According to the method, various information of the face in the video, such as illumination, background, face key points, expressions and the like, is comprehensively extracted, so that the quality of the video generated in video replacement is improved.

In various examples, systems and methods are disclosed relating to accurately extracting requested portions of video data by concatenating video data with selective transcoding. The systems can receive a request indicating a start position and an end position and select a video data element including the start position. The systems can decode a portion of the video data element including the start position and encode a subset of a plurality of first frames of the video data element to provide a first video output. The systems can combine the first video output with a second video output that includes one or more second frames of the video data up until the end position.

A system and a method for displaying super-resolution images generated from images of lower resolution, includes processor circuitry for a combination multi-core CPU and machine learning engine configured with an input for receiving the low resolution images, a feature extraction section to extract features from the low resolution images, non-linear feature mapping section, connected to the feature extraction section, generating feature maps using a self-calibrated block with pixel attention having a plurality of Depthwise Separable Convolution (DSC) layers, a late upsampling section combines at least one DSC layer and a skip connection that upsamples the feature maps to a predetermined dimension, and a video output for displaying approximate upsampled super-resolution images that corresponds to the low resolution images.

Consistent with disclosed embodiments, systems and methods for analyzing video output streams and generating a primary video stream may be provided. Embodiments may include automatically analyzing a first video output stream and a second video output stream, based on at least one identity indicator, to determine whether a first representation of a meeting participant and a second representation of a meeting participant correspond to a common meeting participant. Disclosed embodiments may involve evaluating the first representation and the second representation of the common meeting participant relative to one or more predetermined criteria. Embodiments may involve selecting, based on the evaluation, either the first video output stream or the second video output stream as a source of a framed representation of the common meeting participant to be output as a primary video stream. Furthermore, embodiments may include generating the primary video stream including the framed representation of the common meeting participant.

Echocardiography deep learning and cardiovascular outcomes are described. An echocardiogram analysis module may include a deep learning model to generate a video output for an input echocardiogram video, the deep learning model comprising a convolutional neural network and at least one dense layer. The echocardiogram analysis module may further include a cardiac prediction generator to generate a cardiac prediction based on video outputs generated for a plurality of input echocardiogram videos of an echocardiogram study, the cardiac prediction comprising a measurement prediction or a classification prediction.

The embodiment of the invention relates to the technical field of computer vision, in particular to an RGBT target tracking method based on frequency space enhancement and time adaptation, which comprises the following steps: obtaining a training sample set which comprises a plurality of video sequences, and each video sequence is composed of a visible light image and a thermal infrared image which are paired; constructing an RGBT target tracking model based on frequency space enhancement and time adaptation, wherein the RGBT target tracking model is composed of a frequency space enhancement network, a cross-modal feature extraction network and an online score prediction network; performing iterative training on the RGBT target tracking model based on the training sample set until convergence to obtain a trained model; and inputting the target video into the trained model to obtain a tracking result of the target video output by the trained model. According to the method, the coping capacity of RGBT target tracking in challenging scenes such as background interference and thermal crossover can be well improved, and the accuracy, efficiency and robustness of RGBT target tracking are effectively improved.

The invention discloses an auxiliary screen driving method and system based on a virtual display architecture, and the method comprises the steps: creating virtual display which takes an image output target as a rendering terminal in a system layer; preferentially acquiring the latest available composite frame at each display synchronization beat; performing content change detection on the current frame and the previous frame to determine an area to be updated; adaptively adjusting a target frame rate, an output resolution, a difference threshold value and / or update block granularity of virtual display based on the operation states of the auxiliary screen transmission link and the frame queue; scheduling the differential updating sequence according to regional importance, and preferentially ensuring that a region containing user interface elements is transmitted in time; using synchronous isolation to limit a synthesis and submission path of virtual display; and sending the differential update to the secondary screen through the point-to-point communication link to complete display refresh. According to the technical scheme, on the premise of not depending on additional video output hardware, the double-screen display capacity with controllable cost, compatibility with a native architecture and higher robustness is achieved.

Audio / video base stations may include a plurality of audio / video input ports. The base stations may include an audio / video output port. The base stations may include a communication interface that is coupleable with an audio transceiver. The base stations may include one or more processors. The base stations may include a memory device having instructions stored thereon that, when executed by the one or more processors, cause the audio / video base station to detect that the audio transceiver has been undocked from the audio / video base station. The instructions may further cause the base station to, in response to detecting that the audio transceiver has been undocked from the audio / video base station, automatically switching an audio output signal from the audio / video output port to the communication interface while continuing to transmit a video output signal to the audio / video output port.

Echocardiography deep learning and cardiovascular outcomes are described. An echocardiogram analysis module may include a deep learning model to generate a video output for an input echocardiogram video, the deep learning model comprising a convolutional neural network and at least one dense layer. The echocardiogram analysis module may further include a cardiac prediction generator to generate a cardiac prediction based on video outputs generated for a plurality of input echocardiogram videos of an echocardiogram study, the cardiac prediction comprising a measurement prediction or a classification prediction.

The invention discloses a method and a system for automatically generating a video based on multi-agent unstructured knowledge, and relates to the technical field of video automatic generation based on knowledge processing, and through a data source weight evaluation mechanism and a content semantic similarity calculation method, repeated or contradictory knowledge fragments are automatically identified, a disputed knowledge unit list is established, and the video is automatically generated according to the disputed knowledge unit list. And analyzing the matching degree of the dispute content and the preset script by adopting a semantic vector similarity algorithm. And for the recognized dispute knowledge points, a standby knowledge replacement algorithm is applied to retrieve replacement contents with high confidence from a reliable knowledge base, a knowledge unit replacement operation is executed, and high-quality video output with dispute identification is generated, so that the content accuracy and credibility of the multi-source knowledge fusion video are effectively improved. According to the method, a whole-process quality control system from knowledge identification to video generation is established, intelligent matching of knowledge credibility evaluation and a video content presentation mode is realized, and practical deployment of the technology is restricted.