1008 results about "Bit rate" patented technology

The invention relates to the technical field of streaming media decoding, and discloses a streaming media decoding method and device for a network high-definition player and a storage medium, and the method comprises the steps: carrying out the multi-thread parallel collection and storage of real-time temperature data, network bandwidth jitter data and video code rate fluctuation data of a decoding chip in the network high-definition player; obtaining a streaming media dynamic feature data set; performing classification training to obtain an inter-frame correlation prediction model; constructing a multi-stage streaming media caching system based on the inter-frame correlation prediction model; monitoring a cache state, a network state and a chip state in the multi-stage streaming media cache system in real time to obtain a decoding event sequence; according to the decoding event sequence, the decoding parameter is adjusted in real time, and the streaming media decoding control instruction is obtained.The collaborative optimization of a network layer, a decoding layer and a display layer is achieved, the playing starting delay is reduced, and the overall stability of a network high-definition player is improved.

The invention relates to the technical field of vehicle network control, in particular to an efficient vehicle network control system and method based on CAN-FD, and the system comprises a data transmission optimization module, a bandwidth management module, a signal scheduling control module, an encryption security control module and an anomaly detection module. In the invention, the bit rate of a data frame, the length of a data packet and the proportion of filling bytes are optimized, the transmission efficiency is improved, the bandwidth occupied by invalid data is reduced, a priority screening mechanism is called, the stable transmission of high-priority signals is ensured, the bandwidth allocation is adjusted based on the flow state and node frequency monitoring, the burst flow congestion is relieved, and the resource allocation is balanced; in combination with arbitration priority and bus conflict state, non-emergency signal priority is optimized, key data blocking risk is reduced, encryption and integrity verification are adopted, data security is ensured, tampering and leakage are prevented, data abnormity score and detection are introduced, abnormal data are screened, identification capability is improved, and network potential safety hazard is reduced.

The invention relates to the technical field of wireless high-definition audio and video transmission, and discloses a plug-and-play wireless high-definition audio and video transmission method and system.The method comprises the steps that foreground space texture features and audio and voice segments are obtained, and an initial feature set containing space and semantic features is obtained through semantic correlation analysis; a unified representation vector is output through multi-modal feature fusion, and a dynamic importance score is obtained by determining time sequence consistency, calculating an importance weight and performing normalization; and when the score exceeds a threshold value, segmenting the video frame in real time to determine an attention focus area and optimize a boundary, thereby generating an attention weight matrix, preferentially allocating bandwidth and forming a partition differentiation compression result. And in combination with a network bandwidth state, protection is enhanced for a key stream, the priority and the bit rate are dynamically adjusted, and high-quality audios and videos are output through decoding and recombination. According to the invention, the bandwidth allocation and compression strategy can be dynamically optimized, the transmission quality of a key area is guaranteed when the bandwidth fluctuates, and the audio and video transmission efficiency and experience are improved.

The invention provides a subway train traction energy efficiency optimization data transmission control method and system. The method comprises the following steps: acquiring numerical values of vibration parameters when a traction motor of a subway train runs, and segmenting the numerical values of the vibration parameters according to preset time granularity; calculating a comprehensive weight index of each time sequence unit based on the vibration amplitude, the frequency distribution and the phase angle parameter, and generating a dynamic code rate hierarchical allocation strategy in combination with the real-time state of the network transmission bandwidth and a control instruction reservation mechanism; and establishing a multi-dimensional parameter association model based on the numerical value of the vibration parameter, a dynamic code rate hierarchical allocation strategy, the real-time power state of each power electronic device, and the torque output instruction and energy recovery threshold feedback parameter, and dynamically adjusting a data transmission rule through the multi-dimensional parameter association model. According to the technical scheme provided by the invention, the accuracy of subway train traction energy efficiency optimization data transmission control is improved.

The invention belongs to the field of image / video compression, and discloses an intelligent image compression encoder based on a conditional reversible neural network, which comprises an image enhancement module, a reversible multi-frequency fusion network RMFFN and an entropy model, and is characterized in that the image enhancement module comprises a multi-expansion channel refiner module MDCR and an expansion residual attention module RDAM; the image enhancement module optimizes input features and constructs a conditional reversible neural network by using a flow model, namely, multi-stage nonlinear mapping is realized by stacking four reversible multi-frequency fusion networks; the super-prior codec of the entropy model extracts hidden variable features by stacking multi-scale residual attention blocks, and introduces a discrete Gaussian mixture likelihood model in an entropy coding stage. According to the method, high-fidelity reconstruction is still kept at a low bit rate, and the technical problems of bit rate-distortion balance, high-frequency detail retention and calculation efficiency of a traditional method are solved.

A communication method is described that receives, by a policy control network element, a quality of service (QoS) request message from an application function network element. The QoS request message comprises a QoS requirement of a service of the application function network element. The policy control network element based on the QoS requirement, determines M policy and charging control (PCC) rules corresponding to the service, wherein N of the M PCC rules comprise first indication information, the first indication information indicates data flows of the service corresponding to the PCC rules comprising the first indication information to share a bit rate of the service. The N PCC rules are mapped to at least two QoS flows used to carry the data flows of the service, M and N are integers greater than 1, and N is less than or equal to M. The policy control network element sends the M PCC rules to a session management network element.

A UE may be configured with an enhanced network throughput for data transmission with a small burst or a low burst. In one aspect, for the network throughput estimation for an UL transmission with a small burst, the UE may calculate the burst duration by excluding the SR lead time from the burst period. In another aspect, for the network throughput estimation for a window with the low burst duration, the UE may calculate a scaling factor between the channel bit rate and the estimated network throughput of a time window with a sufficient burst duration and estimate the network throughput of the low burst duration based on the estimated channel bit rate and the scaling factor. In another aspect, to improve the overall process of the network throughput estimation, the UE may dynamically adjust the associated parameters by comparing the estimated network throughput with a base throughput.

The invention relates to the field of network communication, and particularly discloses a network self-adaptive video conference transmission optimization method and system, and the method comprises the steps: systematically analyzing a historical data sequence of a network state, and extracting a deep trend and mode of a network behavior from the historical data sequence; meanwhile, different requirements of the type of the current conference video frame on transmission parameters (especially code rates) are fully considered, and the key information is fused into a decision-making process. Through a specially designed fusion model, the historical evolution trend of the network state and the specific requirement of the current video content can be intelligently subjected to interactive perception and cooperative processing, so that a video target code rate which can adapt to future network fluctuation and can meet the current picture quality requirement is generated. Based on the dynamically optimized target code rate, the system further determines an appropriate target resolution and an appropriate target frame rate, and the video is coded and transmitted.

The present disclosure relates to the technical field of computers. Disclosed are a video processing method and apparatus, and electronic device, and a storage medium. The method provided by the present disclosure comprises: obtaining a current video frame and a current bandwidth corresponding to the current video frame; performing bit rate prediction on the basis of video frame information and a target quantization parameter to obtain a predicted bit rate of the current video frame, wherein the video frame information comprises a content analysis result of the current video frame and / or frame information of a previous output frame, and the previous output frame is an output frame corresponding to a previous video frame; determining a target bit rate of the current video frame on the basis of the predicted bit rate and the current bandwidth; and encoding the current video frame on the basis of the target bit rate, and determining a current output frame. The method realizes dynamic adjustment of a bit rate of an encoder, and avoids bandwidth resource waste when a definition objective is met.

The embodiment of the invention provides a voice coding method and decoding method based on time sequence modeling and a related device. The voice coding method comprises the following steps: acquiring target voice; extracting voice features corresponding to the voice waveform of the target voice through an input cavity convolution extraction module; performing down-sampling processing on the voice features through a down-sampling module to obtain a down-sampling sequence; performing long time sequence modeling on the down-sampling sequence through a long and short time memory neural network added with exponential activation and matrix operation to obtain a coding sequence; and converting the feature dimension of the coding sequence into 128 dimensions through the first convolutional layer to obtain a target code stream. According to the embodiment of the invention, the feature extraction module, the down-sampling module, the long and short term memory neural network and the output cavity convolution layer code the target voice, so that the compression of the voice with the extremely low bit rate can be realized, and the reconstruction of the voice with the extremely low bit rate and high quality under 150bps is realized.

The invention discloses a code rate adaptive image compression method and system, and the method comprises the steps: obtaining an input image, and calculating the local information entropy of the input image to generate a spatial adaptive mask; obtaining target code rate and actual code rate information to generate a code rate control signal; and dynamically selecting a calculation path by using a mask through a dynamic reversible neural network, and executing reversible quantization transformation according to the control signal to obtain a compressed bit stream and actual code rate information for closed-loop feedback. According to the method, a symmetric reversible framework with shared parameters is constructed, so that the model storage requirement is reduced; the calculation depth of the network is dynamically adjusted through entropy sensing gating, and the overall calculation amount is reduced; and a composite control and PID optimization mechanism is adopted, so that continuous and smooth code rate control is realized. The deployment and application efficiency of the compression system in a resource limited scene can be effectively improved.

The invention provides a video coding method and device, electronic equipment and a storage medium, relates to the technical field of image processing, in particular to the field of video coding and the like, and can be applied to application scenes such as video live broadcast and the like. The specific implementation scheme is as follows: acquiring a reference frame which is adjacent to a current frame and has established initial ROI hierarchical division; multiplexing a motion vector generated by the reference frame in a motion compensation time domain filtering process, and determining an ROI position predicted value of the current frame; extracting feature points of the five sense organs of the current frame, and correcting an ROI position predicted value based on a feature point spatial topological relation in the initial ROI; respectively configuring differential quantization parameters for the corrected main face region, the corrected secondary face region and the corrected background region; dynamically allocating a three-layer area code rate according to a real-time network bandwidth; and outputting the coded frame of the current frame and the associated ROI level metadata. According to the scheme, the coding efficiency and quality can be improved.

A method and system for controlling advertisement-exposure monitoring. An example method includes (i) a computing system receiving digital query signature data representing media presented at a given time at a panelist site, (ii) the computing system determining, based on network-monitoring at the panelist site, that, at the given time, the panelist site was receiving a non-zero packet-data flow that had a bit rate too low to be program-content streaming, and (iii) responsive to at least the determining, the computing system searching through advertisement reference signature data for a match, between the advertisement reference signature data and the digital query signature data, that would establish that the media presented at the given time was a given advertisement.

The invention relates to the technical field of streaming media, in particular to an energy-saving video adaptive bit rate optimization method based on deep reinforcement learning, which introduces a video quality evaluation method of video multi-method fusion evaluation in the optimization process, effectively evaluates the perception quality of a video at different bit rates, and improves the video quality. It is ensured that the user obtains the most real picture experience in the watching process; meanwhile, an energy consumption perception model is provided by combining a neural network of an Actor-Critic architecture, and the energy consumption condition of equipment in the video playing process is estimated based on the energy consumption of video data downloading and video rendering; besides, by improving an entropy updating strategy of a near-end strategy optimization algorithm, multi-dimensional information such as network conditions and user preferences is combined more effectively, the bit rate decision of the video stream is optimized, and the video quality and the energy consumption are balanced. According to the invention, on the premise that the user experience quality is ensured, the equipment energy consumption is obviously reduced, so that the dual optimization of the video stream transmission quality and the energy consumption is realized.

The invention discloses an intelligent set top box video processing system based on multimode decoding, which relates to the field of terminal video processing, and comprises the following steps: an original data stream processing module outputs a scene complexity grading label through a spectral clustering algorithm; the video metadata analysis module is used for analyzing metadata of an original video stream in real time and identifying a content type identifier; the edge-cloud cooperative decoding module allocates the high-complexity video frames to edge nodes for decoding, allocates the low-complexity video frames to a local terminal for decoding, and outputs a decoded video frame sequence; the video restoration module detects and restores picture distortion caused by transmission frame loss or signal interference; the dynamic code rate control module dynamically distributes the code rate weight of each block-level area according to the scene complexity grading labels; and the energy efficiency self-optimization module dynamically controls the states of the heating sheet and the idle decoding channel to adjust the core voltage and the decoding frame rate of the CPU. The method has the advantages of low power consumption, strong adaptability to weak network smoothness through multi-scene high-definition cloud edge collaboration.

The invention relates to the technical field of digital televisions, in particular to an intelligent recommendation remote propaganda and distribution system, which comprises a content analysis module for calculating a movement speed value, a color contrast value and a texture complex value in a video picture and generating a scene feature index. According to the method, the motion speed value, the color contrast value and the texture complex value in the video picture are refined, the scene feature index is comprehensively generated, and the regional importance matrix is generated in combination with the regional division information, so that the characteristics and priorities of different video regions are analyzed, and the resource allocation has dynamic adaptability; and the configuration of the code rate and the resolution ratio is optimized in a targeted manner. Through real-time acquisition and spatial mapping of the user sight direction and the head motion data, the user view range is generated and is subjected to superposition calculation with the regional importance matrix, so that regional resource allocation can focus on the region of interest of the user, and the pertinence and effectiveness of content delivery are improved.

A method includes recording a first bitrate of a data transfer session between a user endpoint device and a network element of a terrestrial mobile network, wherein the user endpoint device is locked into a radio frequency band of the terrestrial mobile network, recording a second bitrate of the data transfer session, during a test interval in which a satellite of a non-terrestrial network that shares the radio frequency band with the terrestrial mobile network is executing a function that generates a data transmission to generate full-bandwidth noise signals, calculating a difference between the first bitrate that is recorded and the second bitrate that is recorded, and initiating, in response to the difference exceeding a threshold, an action to modify a parameter of at least one of the terrestrial mobile network or the non-terrestrial network to reduce an effect of channel interference resulting from the sharing of the radio frequency band.

The invention provides a distortion and perceptual code rate self-adaptive variable code rate depth image compression method, which is used for constructing an encoder model, and comprises the following steps of: dividing an image to be encoded into image blocks with different granularities, extracting hierarchical features, and filtering by using an image mask to obtain non-repetitively represented hierarchical features; vector quantization is carried out on the hierarchical features based on the hierarchical vector quantization codebook, and discrete index representation is generated and coded into a code stream file; constructing a decoder model, namely decoding a code stream file into discrete index representation, recovering layered features through a layered vector quantization codebook, fusing and decoding by using a mixed condition decoder, and generating a reconstructed image; carrying out joint training on the encoder model, the decoder model and the layered vector quantization codebook; and encoding an input image into a code stream file through the trained encoder model, and decoding the code stream file into a reconstructed image through the trained decoder model. According to the invention, fine bit rate control and adaptive switching between perception and distortion optimization can be realized.

The invention provides a code rate control method, and the method comprises the steps: updating the deviation information between an accumulated data volume in a preset time period corresponding to a first image frame and a target data volume according to the data volume of the first image frame currently encoded by an encoder; wherein the accumulated data volume is determined according to the total data volume of the plurality of image frames coded in the preset time period, and the target data volume is determined according to the target code rates of the plurality of image frames; under the condition that it is determined that the first image frame belongs to a waiting frame, if the deviation information is larger than a forced adjustment threshold value, a code rate adjustment instruction is triggered, and the code rate adjustment instruction is used for instructing the encoder to adjust the encoding code rate of the to-be-encoded image frame; wherein the forced adjustment threshold value is greater than a conventional adjustment threshold value, and the conventional adjustment threshold value is used for determining whether to trigger a code rate adjustment instruction or not under the condition that the current image frame does not belong to a waiting frame. According to the mode, dynamic balance of code rate control can be realized through a double-threshold triggering mechanism.

The invention discloses an extremely low bit rate image compression coding and decoding method of a stream matching diffusion model. The coding method comprises the following steps: acquiring an original image, and coding the original image into a compression latent variable and a hierarchical feature; based on the compression latent variable, generating an anchor point set and a mask parameter in a continuous domain; generating a visible index, a stream matching scheduling parameter and a confidence graph according to the compression latent variable, the hierarchical feature and the target bit rate; and combining the visible index, the anchor point set, the mask parameter, the stream matching scheduling parameter and the confidence map to form a code stream. According to the invention, through continuous domain mask and confidence gating reasoning of code rate perception, the method is suitable for image compression with an extremely low bit rate.

In some embodiments, a method determines whether to use first logic or second logic to select a profile from a list of profiles to download a segment of content. When using the second logic: selecting historical information from one or more previous playback sessions; determining a bandwidth using the historical information; and selecting the profile using a bitrate that is determined based on the bandwidth. When using the first logic, selecting the profile without using the historical information.

The invention discloses a novel digital hybrid coding method based on a large model. The method comprises the following steps: S1, preprocessing to-be-coded data; s2, performing feature coding on the preprocessed data by adopting a diffusion model driven feature learning method; s3, performing neural network coding on the feature coding data, and dynamically adjusting the coding bit number based on a variable bit rate quantization method; s4, performing adaptive entropy coding on the neural network coding data, and performing probability density transformation based on a normalized flow entropy coding method; s5, discrete transform coding is carried out on entropy coding data, and hierarchical quantization is carried out on different frequency components by adopting a hierarchical sub-block quantization method; and S6, based on the code length distribution and entropy coding parameters of the A3C optimization transformation coding data, extracting a lightweight coding model from the diffusion model by using a knowledge distillation method, and generating final optimization coding data. Through the hybrid coding and dynamic optimization strategy, the data compression efficiency and the coding quality are remarkably improved.

Various embodiments provide methods, apparatuses, and computer program products. An example apparatus includes: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to perform: using a codec for coding an input to a first bitrate and / or a first reconstruction quality; using the codec for coding the input to a second bitrate and / or a second reconstruction quality; wherein the first bitrate is different from the second bitrate; and / or wherein the first reconstruction quality is different from the second reconstruction quality.

A communication method and a communication apparatus. In the method, a transmit end obtains to-be-encoded information, where the to-be-encoded information includes k bits, and k is a positive integer; the transmit end determines that a quantity of code blocks is C, and C is a positive integer; the transmit end performs polar encoding on the to-be-encoded information based on C, to obtain C encoded code blocks; and the transmit end sends the C encoded code blocks. In some implementations, the transmit end determines, based on k and a target bit rate, that the quantity of code blocks is C. In some implementations, the transmit end obtains the C encoded code blocks in a code block coupling manner.

Interleaving of variable bitrate streams for GPU implementations is described. An example of an apparatus includes one or more processors including a graphic processor, the graphics processor including a super-compression encoder pipeline to provide variable width interleaved coding; and memory for storage of data, wherein the graphics processor is to perform parallel dictionary encoding on a bitstream of symbols one of multiple workgroups, the workgroup to employ a plurality of encoders to generate a plurality of token-streams of variable lengths; create a histogram including at least tokens from the plurality of token-streams for the workgroup to generate an optimized entropy code; entropy code each of the plurality of token-streams for the workgroup into an encoded bitstream; and variably interleave the encoded bitstreams to generate an interleaved bitstream and bookkeep a size of the interleaved bitstream.

A method includes acquiring a playlist identifying a plurality of video files to be played back during a video streaming session on an endpoint device, obtaining, from an operator of a communications network over which the video files are to be downloaded, a maximum throughput for the video streaming session, selecting a subsequent video file that is scheduled in the playlist for playback after a playback of a currently playing video file, wherein the subsequent video file includes a plurality of chunks, selecting, based on the maximum throughput and for each of the chunks, a variant, such that a plurality of variants is selected in which each variant corresponds to one chunk of the plurality of chunks, wherein the variants are selected to maximize a utility function that is constrained by the maximum throughput, and downloading the plurality of variants to a local buffer of the endpoint device.

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.

Systems and methods are disclosed for generating an adaptive bitrate ladder for a content item based on the actual quality of the content item. A user uploaded content item is determined to have different quality scores in different time portions of the content item, where the quality score is based on an analysis of visual characteristics of frames of the content item. In response, an adaptive bitrate ladder (ABR) is generated for each time portion which contains a set of bitrates based on the quality score.

The invention relates to the technical field of data processing, in particular to a data transmission method and device and encoding equipment. The method comprises the following steps: receiving video source data, and performing data compression on the video source data according to a first code rate and a second code rate to obtain first data corresponding to the first code rate and second data corresponding to the second code rate; wherein the value of the first code rate is smaller than that of the second code rate; and transmitting at least one first data packet in the first data and at least one second data packet in the second data in turn until the first data and the second data are transmitted completely.

The invention discloses a point cloud compression method based on multi-dimensional feature fusion, electronic equipment and a medium, and aims to effectively reduce the compression bit rate while maintaining the precision of a space structure. According to the method, space, channel and topology redundant information is fused under a unified framework for the first time, and the method is suitable for efficient point cloud compression of various three-dimensional scenes such as automatic driving and virtual reality. Meanwhile, a local graph convolution Mama module is introduced, and the limitation that a point cloud topological structure is difficult to capture in a traditional method is effectively solved. Then, the octree nodes are divided into two dimensions of space and channel through a space-channel coupling grouping module, so that gradual feature fusion is realized, and the context information prediction precision is improved; experimental results show that the compression efficiency is remarkably improved on a plurality of radar and voxel human body model data sets.