347 results about "Filter (video)" patented technology

A video coding mechanism is disclosed. The mechanism includes receiving a bitstream comprising a current picture including a sub-picture coded according to inter-prediction. A motion vector for a block of the sub-picture is determined. A clipping function is applied to sample locations in a reference block to support application of an interpolation filter when the motion vector points outside of the sub-picture and when a flag is set to indicate the sub-picture is treated as a picture. The interpolation filter is applied to results of the clipping function to obtain a predicted sample value. The block is decoded based on the predicted sample value. The block is forwarded for display as part of a decoded video sequence.

An example method of video coding includes receiving a video bitstream comprising a plurality of frames, including a current frame comprising a current block. The method also includes determining an edge direction by performing edge detection for the current block, and determining a difference between a current sample of the current block and a neighboring sample based on the edge direction. The method further includes applying a filter to the current block based on the determined difference.

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.

Approaches presented herein provide for the high quality, high resolution reconstruction of a sequence of decimated images, such as may be useful for remote desktop applications. The video frames can be sub-sampled or decimated such that each encoded frame only includes a fraction (e.g., ¼) of the total pixel values for the full resolution frame. A server can analyze the current and previous video frames at full resolution to determine motion or actionable changes, and can apply a lowpass filter to those values based on the type of interpolation to be performed on the client. Static values can remain where no motion is detected. When a client receives the decimated and encoded video frames, the client can determine areas of motion and can perform bilinear interpolation for only those portions of the image where motion is detected, and can otherwise perform weaving of the static pixel values received over a limited sequence of decimated video frames.

The invention discloses a vehicle violation manned intelligent detection method and system based on a CLIP and D-Fine cascade framework, and the method comprises the steps: collecting a real-time video frame image of a preset traffic monitoring network, processing the real-time video frame image, inputting a monitoring image into a CLIP-ILP model, employing the CLIP-ILP model as a filter, and combining with a Top-K screening strategy, and screening out candidate images; and inputting the candidate image into a constructed context enhanced D-FINE detection model, carrying out positioning and multi-class detection on a preset target, outputting a multi-class detection result, and executing verification of a spatial co-occurrence rule, a license plate position heuristic rule, a size consistency rule and a context consistency rule. And marking the result which does not pass the verification as suspicious or rejecting the result, and outputting the result which passes the verification as an illegal manned detection result to the target terminal. According to the method, the problem of balance between the recall rate and the precision in manned detection can be solved.

An apparatus comprising an interface and a processor. The interface may be configured to receive pixel data of an environment. The processor may be configured to process the pixel data arranged as video frames, generate a luminance distribution map of the video frames in response to a low-pass filter operation, determine a plurality of defogging intensity weights for the luminance distribution map, perform adaptive smoothing to each of the plurality of defogging intensity weights, and generate defogged video frames in response to the video frames and the plurality of defogging intensity weights with the adaptive smoothing. The plurality of defogging intensity weights may each correspond to one of a plurality of luminance intervals of the luminance distribution map. The adaptive smoothing may be configured to prevent brightness differences in the defogged video frames.

A mechanism for processing video data is disclosed. The mechanism includes determining to signal a processing order or a preferred processing order of different post-processing filters, including zero or more neural-network post-filters (NNPFs) and zero or more non-NNPF post-processing filters, in a supplemental enhancement information (SEI) processing order SEI message. A conversion is performed between a visual media data and a bitstream based on the SEI processing order SEI message.

A method and an apparatus are disclosed for video coding CC-ALF based on a nonlinear cross-component relation. A video decoding device obtains a reconstructed frame that is an output of a sample adaptive offset (SAO) filter and generates an adaptive loop filter output (ALF output) by inputting the reconstructed frame into an adaptive loop filter (ALF). The ALF output includes a luma ALF output and a chroma ALF output. The video decoding device generates corrected values of a chroma component by inputting the luma ALF output into a nonlinear cross-component ALF (nonlinear CC-ALF) and generates an enhanced chroma ALF output by summing the corrected values of the chroma component and the chroma ALF output.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing comprises: determining, from a plurality of filter shapes during a conversion between a current video block of a video and a bitstream of the video, a first filter shape for coding a first sample of the current video block; and performing the conversion based on the first filter shape. Compared with the conventional solution, the proposed method can advantageously improve the performance of the filtering tool.

A video encoder and video decoder are configured to determine a filter from a first temporal layer having a first temporal layer ID, determine a scaling factor for the filter from a second temporal layer having a second temporal layer ID, and store the scaling factor in a buffer for future usage based on the second temporal layer ID being less than or equal to the first temporal layer ID.

A video capture device may be encode a set of original pictures to create encoded video data, decode the encoded video data to create a set of reconstructed pictures, determine a subset of parameters to update from among a plurality of parameters of a post-processing filter network, including using the set of original pictures as ground truth and the set of reconstructed pictures as input to the post-processing filter network, update the subset of parameters to generate updated parameters, and send the encoded video data and the updated parameters to a playback device.

This disclosure relates generally to video coding / decoding and particularly for spatial downsampling and / or resampling in video coding and / or decoding systems. One method includes obtaining, by a device, a coded video bitstream; determining, by the device from the coded video bitstream, a spatial resampling flag for a picture frame; and when the spatial resampling flag indicates that spatial resampling is enabled for the picture frame: determining, by the device from the coded video bitstream, an index indicating a spatial resampling filter, and decoding, by the device, the coded video bitstream by generating spatial resampling data based on the spatial resampling filter.

The invention discloses an advertisement implantation method and system for a short video scene, and the method comprises the steps: generating a time-aligned visual-auditory-text three-path basic representation sequence through frame-by-frame multi-channel perceptual analysis; a semantic scene map and an emotional rhythm curve are constructed, and content narrative logic and psychological tension changes are described; fusing the historical interaction behavior sequence of the user, and generating an individualized attention maintenance model and a preference response field; screening candidate anchor points at the intersection of the content structure and the user state, generating three types of implantation forms, and quantifying the consistency of the implantation forms and adjacent semantic nodes; dynamically determining visual transparency, audio gain multiple, text staying duration and overall continuous span four-dimensional intensity parameters; and after cross-modal consistency verification, a final instruction is generated, and real-time execution and feedback closed loop are carried out. Advertisement becomes natural extension of content semantic evolution and user cognitive rhythm, and attention, understanding and memory are improved on the premise that experience is guaranteed.

The invention relates to a video coding image noise reduction processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring an original video frame image and a step length parameter; dividing the original video frame image into a plurality of pixel units according to the step length parameter; calculating local gradient data for each pixel unit to obtain a local gradient matrix; generating a filtering template according to the local gradient matrix; wherein the filtering template is used for representing a filtering weight of a pixel in the pixel unit; and performing weighted filtering processing on the pixel units according to the filtering template. By adopting the method, the quality of the video image to be coded can be improved.

A mechanism for processing video data is disclosed. The mechanism determines to apply a bilateral filter and a cross component sample adaptive offset (CCSAO) filter to samples in a current block of a current picture. The bilateral filter includes filter weights that vary based on a distance between surrounding samples and a central sample and differences in intensities of the surrounding samples and the central sample. A conversion is performed between a visual media data and a bitstream based on the bilateral filter and the CCSAO filter.

A mechanism for processing video data is disclosed. The mechanism includes determining to use at least one extended tap in an adaptive loop filter (ALF). A conversion can then be performed between a visual media data and a bitstream based on the ALF. The ALF may also employ a conditional filter shape switch.

Systems and methods for performing liveness detection. A method includes transmitting an image or a video by a threat detector to one or more filters for a first level check for detecting a threat based on analysis of certain characteristics, transmitting the image or the video to one or more special models for a second level check, wherein the one or more special models are configured for detecting multiple types of threats on the image or the video, transmitting the image or the video to a general model ensemble for a third level check to classify the image or the video according to individual features into original and fake, and in response to detecting the threat, registering the threat by the threat detector.

Implementations of the disclosure provide a video processing apparatus and method for performing intra prediction on a video block. The video processing method may include receiving, by a processor, reference samples from a video frame of a video comprising the video block. The video processing method may further include determining, by the processor, a reference sample filter based on a size of each video block. The reference sample filter is among a plurality of reference sample filters each derived for a different video block size. The video processing method may also include applying, by the processor, the determined reference sample filter to the received reference samples. The video processing method may additionally include performing, by the processor, the intra prediction on the video block using the filtered reference samples.

Methods, apparatus, and non-transitory computer-readable storage media for video decoding and encoding are provided. In a method for video decoding, a decoder may: determine a non-adjacent neighboring block of a current inter-coded block, where the non-adjacent neighboring block includes a plurality of reconstruction sample points that are non-adjacent to the current inter-coded block; obtaining a plurality of prediction sample points of the non-adjacent adjacent blocks based on the motion vectors of the non-adjacent adjacent blocks; obtaining a filter based on the plurality of prediction sample points and the plurality of reconstruction sample points; obtaining a current prediction block based on the motion vector of the current inter-frame coding block; and obtaining a filtered prediction block based on the filter and the current prediction block.

The application discloses a kind of based on edge identification no target cable force identification method, the method includes: cable video acquisition and pre-processing: acquisition cable video, video frame is carried out image gray conversion and is adapted to the multi-scale Gaussian filtering operation of filter scale according to noise characteristics;Canny algorithm cable edge identification: using Canny edge detection algorithm to the video frame after pre-processing is carried out cable edge identification;Cable feature point screening and KLT optical flow method identification: from edge identification result screening cable feature point, and using KLT optical flow method in continuous video frame between tracking feature point dynamic displacement;Fundamental frequency identification and cable force calculation: displacement data is applied Fourier transform to identify cable fundamental frequency, and adopts XGBOOST regression model based on fundamental frequency and relevant parameter calculation cable tension.The application realizes the precise, efficient and non-contact monitoring of bridge cable stress state.

An example apparatus for filtering decoded video data includes: a memory configured to store video data; and one or more processors implemented in circuitry and configured to: decode blocks of video data to form decoded blocks; apply a filter to the decoded blocks to form filtered blocks; multiply samples of the filtered blocks by a scaling factor to form thinned filtered blocks; and combine samples of the thinned filtered blocks with corresponding samples of the decoded blocks. The one or more processors may also encode the blocks prior to decoding them. The one or more processors may encode or decode, for example, the value of a syntax element representing a scaling factor in a picture header including the block.

The present application discloses a video decoding method, a video encoding method, a storage medium, an electronic device and a product. The video decoding method comprises: obtaining a video bitstream, wherein the video bitstream comprises decoding indication information, and the decoding indication information comprises at least one filter flag bit used for indicating a filter parameter; on the basis of a value of the filter flag bit, determining tap coefficient information in the filter parameter; and on the basis of the tap coefficient information, determining the filter parameter.

A method for implementing an adaptive loop filter (ALF) in a video system is provided. A video coder receives data for a block of pixels to be encoded or decoded as a current block of a current picture of a video. The video coder receives a current sample of the current block. The video coder applies a filter to the current sample to generate a correction value. Neighboring samples from two or more different sources are used as inputs to the filter. When a first neighboring sample is within a virtual boundary, the first neighboring sample is used as an input to the filter. When the first neighboring sample is beyond the virtual boundary, the first neighboring sample is precluded as an input to the filter. The video coder adds the correction value to the current sample as a filtered sample of the current block.

Provided is a scalable video-decoding method based on multiple layers. The scalable video-decoding method according to the present invention comprises: a step of predicting first filter information of a video to be filtered using the information contained in an object layer and / or information contained in another layer, and generating second filter information in accordance with the prediction; and a step of filtering the video to be filtered using the second filter information. According to the present invention, the amount of information being transmitted is reduced, and video compression performance is improved.

Embodiments of the present disclosure provide a solution for video processing. A method for video processing is presented. The method comprises: for a conversion between a video unit of the video and a bitstream of the video, determining that one or more parameters of a cross-component residual model (CCRM) of the video unit are inherited from a previous filter-based codec block, where the CCRM is a filter model comprising a cross-component model or the same component model; and performing the conversion based on the CCRM.

The present disclosure provides a method of encoding a video sequence. The method includes receiving a video sequence; encoding the video sequence using an extrapolation filter-based intra prediction (EIP) fusion mode. The encoding the video sequence using the EIP fusion mode includes obtaining a first predictor by an extrapolation filter-based intra prediction (EIP) mode; obtaining a second predictor by an intra prediction mode; generating a fused predictor by fusing the first predictor and the second predictor; and predicting one or more pictures using the fused predictor.

A mechanism for processing video data is disclosed. The mechanism determines to process video information with a high operating point (HOP) filter that includes a deep convolutional layer or a packet convolutional layer. Conversion is performed between the visual media data and the bitstream based on the HOP filter.

The present disclosure provides a method for encoding a video sequence. The method includes receiving a video sequence; encoding the video sequence using an extrapolation filter-based intra prediction (EIP) fusion mode. The encoding the video sequence using the EIP fusion mode includes obtaining a first predictor by an extrapolation filter-based intra prediction (EIP) mode; obtaining a second predictor by an intra prediction mode; generating a fused predictor by fusing the first predictor and the second predictor;and predicting one or more pictures using the fused predictor.