395results about "Video signal spatial resolution conversion" patented technology

A method includes obtaining, using at least one processing device of an electronic device, a video including multiple scenes at a first aspect ratio. The method also includes performing, using the at least one processing device, backward optical flow estimation and forward optical flow estimation for each of the multiple scenes to select an image frame having a largest missing area. The method further includes performing, using the at least one processing device, outpainting on the image frame having the largest missing area to generate a first outpainted image frame at a second aspect ratio different from the first aspect ratio. In addition, the method includes performing, using the at least one processing device, backward optical flow estimation and forward optical flow estimation using the first outpainted image frame to generate additional outpainted image frames in the multiple scenes at the second aspect ratio.

In various examples, systems and methods are disclosed relating to aligning images into frames of a first video using at least one first temporal attention layer of a neural network model. The first video has a first spatial resolution. A second video having a second spatial resolution is generated by up-sampling the first video using at least one second temporal attention layer of an up-sampler neural network model, wherein the second spatial resolution is higher than the first spatial resolution.

The invention relates to the technical field of digital twinning, particularly provides a digital twinning scene adaptive optimization method based on point cloud data, and solves the problems that smoothness and detail presentation cannot be balanced during network fluctuation, and a scene prediction optimization mechanism based on space-time semantic analysis is not established. The method comprises the following steps: data preprocessing and hierarchical construction: carrying out preprocessing of abnormal point elimination, missing value complementation and density adjustment on original point cloud data, dividing key and common regions according to scene requirements, and constructing a multi-scale and multi-resolution hierarchical point cloud data system; the method can deeply analyze the spatio-temporal dynamic characteristics of the point cloud data through the technologies of spatio-temporal dynamic semantic segmentation, dynamic change monitoring, prediction optimization and the like, processes the continuous time sequence point cloud data after adaptive transmission, models a time dependency relationship and extracts local and global characteristics in time and space dimensions respectively, and improves the accuracy of point cloud data processing. Accurate identification of object types, positions and dynamic change information is realized.

Provided are a method for enhancing a video resolution enhancement, a computer readable storage medium, and an electronic device. The method includes: obtaining multiple image frames as input data, and obtaining initial data by performing feature extraction on the input data using a first three-dimensional convolutional layer; obtaining first feature data by performing down-sampling on the initial data at a preset multiple; obtaining first reference data by performing a convolution operation on the first feature data using a second three-dimensional convolutional layer to merge the first feature data as one frame; and obtaining first output data by performing up-sampling on the first reference data at the preset multiple.

A signal processing method includes obtaining an image signal and a first event signal that are of a target scene, where the first event signal is an event signal in a frame format or a stream format; performing time-dimension and / or space-dimension format conversion on the first event signal, to obtain a second event signal, where the second event signal is an event signal in a frame format; and fusing the second event signal and the image signal, to obtain a fused signal.

A multimedia processing method, a multimedia processing apparatus, and a non-transitory computer-readable storage medium are disclosed. The multimedia processing method includes: acquiring an input multimedia, and performing image quality enhancement processing on the input multimedia to obtain an enhanced multimedia. A resolution corresponding to the enhanced multimedia is higher than a resolution corresponding to the input multimedia.

A method of delivering audiovisual content to a viewer includes monitoring a viewer activity, prompting viewer to determine intent upon the occurrence of a pre-specified event, identifying content for delivery based on a response from the viewer and selectively delivering the content to the viewer, wherein the delivery is via a broadband connection during a non-peak data traffic time.

The invention relates to a parameter adjustment method and device, electronic equipment and a storage medium. The parameter adjustment method comprises the following steps: determining a target parameter and / or a current display interface of the display equipment; determining an adjustment scene according to the type of the target parameter and / or the current display interface; determining a target adjustment mode according to the adjustment scene; and adjusting display parameters of the display equipment according to the target adjustment mode. According to the embodiment of the invention, by determining the target parameter and / or the current display interface of the display equipment, the adjustment scene and the target adjustment mode are determined, and the display parameter of the display equipment is adjusted according to the target adjustment mode. Therefore, according to the type of the target parameter and / or the current display interface, the target adjustment mode conforming to the adjustment scene can be determined, and the parameter adjustment requirements in different scenes are met.

An image identifying apparatus includes: an obtainer that obtains image data; an image processor that generates test image data by performing resizing to reduce the image data with predetermined aspect ratio distortion; a storage unit that stores a machine learning model used to identify attribute information of the test image data; and an identifier that identifies the attribute information of the test image data, using the machine learning model. The machine learning model includes trained parameters that have been adjusted through machine learning using a training data set including items of second training image data obtained through application of one or more types of aspect ratio distortion including the predetermined aspect ratio distortion to each of items of first training image data, and items of attribute information associated with the items of second training image data.

Provided is a video processing method and system, a video playback system, an apparatus, a device, and a medium in the technical field of video processing, and the method includes: acquiring an input video frame and display parameters of the input video frame when it is displayed, the display parameters including at least one of a video format and a resolution; processing the input video frame into a plurality of output video frames based on the display parameters, each output video frame corresponds to a partial region of the input video frame; and displaying the plurality of output video frames on a plurality of display devices so that the plurality of output video frames are displayed according to the display parameters.

The invention relates to the technical field of digital videos, in particular to an ARM and FPGA collaborative 4K video hard decoding acceleration system and method.The system is composed of an ARM module, an FPGA module, an FPGA external DDR and an AXI bus transmission protocol, specifically, calculation and transmission processes in the 4K video H.265 decoding process are comprehensively optimized through the collaborative advantages of the ARM module and the FPGA module, and the 4K video H.265 decoding speed is improved. CABAC decoding, a motion compensation module and other core decoding tasks are efficiently achieved through the FPGA module, and meanwhile an AXI bus protocol and a Stream FIFO structure are used for optimizing a data carrying and caching mechanism so as to improve the decoding efficiency. Compared with a pure software decoding scheme, the decoding efficiency is improved, and the power consumption in the decoding process is effectively reduced in combination with collaborative optimization of the FPGA and the ARM processor. In addition, through the modular design and the flexible configuration of FPGA resources, the method and the device can also support the decoding requirements expanded to other video standards (such as H.264) or higher resolution.

An image encoding / decoding method, a bitstream transmission method, and a computer-readable recording medium for storing a bitstream are provided. The image decoding method according to the present disclosure is an image decoding method performed by an image decoding device, and may be an image decoding method comprising the steps of: obtaining size information from a neural-network post-filter characteristics (NNPFC) supplemental enhancement information (SEI) message; and determining the size of an output picture on the basis of the size information, wherein the size information comprises information on the numerator value of the ratio between the size of the output picture and the size of an input picture and information on the denominator value of the ratio.

The invention discloses a high-definition video docking station device, an integrated system and a communication method. The device comprises a main control module, a protocol conversion module, a power management module, a video processing module, a dynamic bandwidth allocation unit, a plurality of video output interfaces and a peripheral expansion unit. The main control module receives an input video signal and performs shunting, compression and protocol analysis; the protocol conversion module manages interface protocol switching, equipment detection and power supply negotiation; the power management module converts input voltage into multi-stage system voltage and provides a reverse charging function; the video processing module is used for splitting an input video signal into multiple paths of independent video streams and reducing the bandwidth; the dynamic bandwidth allocation unit is used for dynamically adjusting the resolution or refresh rate of the video stream; and the peripheral expansion unit is connected with the low-speed peripheral through the independent data channel. The device supports three paths of 4K and 60Hz synchronous output, has high energy efficiency, intelligent bandwidth management and good compatibility, and is suitable for multi-screen cooperation, industrial control and high-resolution display application scenes.

Disclosed herein is zero-latency switching between two resolution and frame rate modes. The system includes receiving a trigger to switch a video data stream of frames between a first resolution and frame rate mode and a second resolution and frame rate mode. The system also includes switching, in response to the trigger, the video data stream between the first resolution and frame rate mode and the second resolution and frame rate mode, wherein a total horizontal pixel width of each frame of the video data stream in the first resolution and frame rate mode and of each frame of the video data stream in the second resolution and frame rate mode are the same, wherein a pixel clock rate of the video data stream in the first resolution and frame rate mode and the video data stream in the second resolution and frame rate mode are the same.

A camera system captures an image in a source aspect ratio and applies a transformation to the input image to scale and warp the input image to generate an output image having a target aspect ratio different than the source aspect ratio. The output image has the same field of view as the input image, maintains image resolution, and limits distortion to levels that do not substantially affect the viewing experience. In one embodiment, the output image is non-linearly warped relative to the input image such that a distortion in the output image relative to the input image is greater in a corner region of the output image than a center region of the output image.

The present invention is related to a wireless multi-stream bidirectional video processing system including: a video input and output device that receives at least one camera video from at least one camera device and performs first processing to the at least one camera video to become a video information; and a video processing device that wirelessly communicates with the video input and output device to receive the video information, performs second processing to the video information to become a plurality of output videos, and transmits the output videos to a host device, wherein the host device outputs at least one display video, and wherein the wireless multi-stream bidirectional video processing system processes the at least one display video to become a device video, and displays the device video on a display device connected to the wireless multi-stream bidirectional video processing system.

A computing system is provided, including a camera configured to capture a series of images in a video stream, processing circuitry, and an image processing pipeline including a preprocessing module and an encoder, in which the preprocessing module is configured to receive the video stream from the camera at a camera-native video data rate parameter. The processing circuitry is configured to communicate with a server to establish a joint video communication session with remote client devices and receive a requested video data rate parameter from the server for the video stream captured by the camera. The processing circuitry is further configured to send a command to the preprocessing module to adjust the camera-native video data rate parameter of the video stream to the requested video data rate parameter and preprocess the video stream at the requested video data rate parameter and pass the preprocessed video stream to the encoder.

The invention discloses a frame rate adjusting method, which is characterized in that an NVR (Network Video Recorder) is driven by an event, and adaptively adjusts the frame rate of each IPC according to the event content of each IPC so as to adjust a code stream, and specifically comprises the following steps: when an IPC is triggered by the event, adjusting the frame rate of the IPC according to the current bandwidth and the equipment parameters of the IPC, and reducing the frame rates of other IPCs which are not triggered by the event for a long time; the video quality is improved by adaptively reducing the frame rate of the IPC when no event is triggered and improving the frame rate when the event is triggered, so that the network bandwidth and the hard disk space are saved, each IPC runs at a lower frame rate when no event is triggered, more IPCs can be accessed to the NVR on the basis of the original maximum bandwidth, and the monitoring quality and the maintenance cost are balanced.

Systems, methods, and computer-readable media are provided for redundantly storing and authenticating event related video data from one or more cameras using a video recording manager device. Additional copies of event related video data are persisted across various storage devices including any combination of internal camera storage, remote storage, and one or more storage mediums associated with the video recording manager device. The stored video data is augmented with authentication metadata to preserve the authenticity such that the video data is suitable as evidence.

In various examples, systems and methods are disclosed relating to aligning images into frames of a first video using at least one first temporal attention layer of a neural network model. The first video has a first spatial resolution. A second video having a second spatial resolution is generated by up-sampling the first video using at least one second temporal attention layer of an up-sampler neural network model, wherein the second spatial resolution is higher than the first spatial resolution.

In some respects, the disclosure is directed to methods and systems for processing signals. A device can include a first circuit configured to process video information for a resolution or scaling operation and provide first data, a second circuit configured to process the video information for the resolution or scaling operation and provide second data, and a third circuit configured to receive the first data and the second data and provide third data according to the resolution or scaling operation, the first circuit comprising a first machine learning engine.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an output video conditioned on an input. In one aspect, a method comprises receiving the input; initializing a current intermediate representation; generating an output video by updating the current intermediate representation at each of a plurality of iterations, wherein the updating comprises, at each iteration: processing an intermediate input for the iteration comprising the current intermediate representation using a diffusion model that is configured to process the intermediate input to generate a noise output; and updating the current intermediate representation using the noise output for the iteration.

The invention relates to the technical field of image communication, in particular to an image processing system and method based on an FPGA, and the system comprises a data stream synchronization module which obtains a video frame and a timestamp through the FPGA; in the invention, the data stream synchronization ensures the matching of the video frame and the timestamp, the stability of the video stream is optimized, the image error caused by time dislocation is reduced, and the accuracy of video analysis is improved. And the transmission priority of the data packet is dynamically set, and the transmission strategy is adjusted according to the importance of the content, so that bandwidth resources are effectively utilized, the priority transmission of key information is ensured, and the overall efficiency and response speed of network transmission are improved. According to the adaptive coding, the coding bit rate and frame rate are dynamically adjusted according to the network condition, the adaptability of the data stream to different network conditions is optimized, and the balance between the video quality and the transmission efficiency is kept. Through the enhancement of image brightness, contrast adjustment and noise suppression, the image quality in a low-light environment is improved, and the availability and viewing experience of the image are improved.

The invention provides an unmanned aerial vehicle video acquisition and return method under multiple time scales. The method comprises the following steps: establishing a first target optimization model and a target constraint condition; the first target optimization model is used for maximizing the quality of the video acquired by the unmanned aerial vehicle; the target constraint condition is used for constraining the non-returned video amount of the unmanned aerial vehicle; and based on the target constraint condition, solving the first target optimization model to obtain an unmanned aerial vehicle video acquisition resolution under the first time scale and bandwidth resources allocated to the unmanned aerial vehicle for video return under the second time scale. According to the method provided by the embodiment of the invention, the video stream data queuing time delay can be reduced through small-time-scale resource allocation, so that the video acquired by the unmanned aerial vehicle can be returned in time, and video jitter caused by frequent video resolution switching can be effectively reduced through large-time-scale video resolution adjustment, so that the video quality is improved. The quality and stability of unmanned aerial vehicle cluster video data acquisition and return are efficiently improved under the limited bandwidth.

A method for processing a video with a dynamic video-based super-resolution network and a circuit system are provided. In the method, quality scores used to assess a quality of an input video are calculated based on image features of the input video. A moving average algorithm is performed on the quality scores of multiple frames of the input video for obtaining a moving average score. Two corresponding weight tables are selected according to the moving average score. The two weight tables are used to calculate a blending weight that is applied to a neural network super-resolution algorithm. The blending weight is applied to the neural network super-resolution algorithm, so as to produce an output video.

The invention provides a low earth orbit satellite network video code rate determination method and device and electronic equipment. The method comprises the following steps: acquiring link state information of a low earth orbit satellite network link; predicting whether a link reconstruction event occurs at the next moment based on the link state information; and under the condition of predicting that a link reconstruction event occurs in the low earth orbit satellite network link at the next moment, dividing a time domain into independent control intervals, and independently determining the video block code rate at the next moment based on the network state of the independent control interval in each independent control interval. According to the method, the satellite network reconstruction event is predicted, and the video code rate is independently determined in the interval mode in the reconstruction event period, so that the video live broadcast experience quality in the low-orbit satellite network environment is improved.

Disclosed herein is zero-latency switching between two resolution and frame rate modes. The system includes receiving a trigger to switch a video data stream of frames between a first resolution and frame rate mode and a second resolution and frame rate mode. The system also includes switching, in response to the trigger, the video data stream between the first resolution and frame rate mode and the second resolution and frame rate mode, wherein a total horizontal pixel width of each frame of the video data stream in the first resolution and frame rate mode and of each frame of the video data stream in the second resolution and frame rate mode are the same, wherein a pixel clock rate of the video data stream in the first resolution and frame rate mode and the video data stream in the second resolution and frame rate mode are the same.

The invention discloses a self-adaptive video transmission control method based on unmanned aerial vehicle bandwidth perception. The method comprises the steps that S1, an unmanned aerial vehicle video system sends a bandwidth perception data frame to a ground receiving end; s2, the ground end returns a bandwidth state data frame, wherein the bandwidth state data frame comprises a received signal strength indication (RSSI) and a frame loss rate (FLR) index; s3, the unmanned aerial vehicle video system analyzes the bandwidth state data frame and evaluates the channel quality grade; s4, the unmanned aerial vehicle video system calculates a buffer proportion factor of the annular buffer area; s5, the unmanned aerial vehicle video system calls a pre-constructed adaptive transmission control model, transmission parameters are updated according to the channel quality grade and the buffer proportion factor, and the transmission parameters comprise transmission video quality and coding parameters; s6, transmitting video data according to the updated transmission parameters of the unmanned aerial vehicle video system; and S7, the ground end receives the video data and decodes and plays the video data. According to the invention, the problem of poor adaptability in different network environments when the unmanned aerial vehicle sends the video data with the fixed channel parameters is solved, and the video transmission quality is improved.

The invention relates to the technical field of video processing, and discloses a video super-resolution reconstruction method and device and wearable equipment, and the method comprises the steps: obtaining a to-be-reconstructed low-resolution video; reconstructing the to-be-reconstructed low-resolution video through a preset reconstruction model to obtain a target high-resolution video; wherein the preset reconstruction model at least comprises a disparity map generation module, and the disparity map generation module is used for determining a reference window and a candidate window of the to-be-reconstructed low-resolution video, performing depth information extraction based on the reference window and the candidate window to generate a disparity map, and reconstructing the to-be-reconstructed low-resolution video according to the disparity map. Compared with the prior art that the depth information is not considered, the method can extract the depth information for reconstruction, thereby improving the reconstruction effect.