Intel Corporation

Tahoe Research, Ltd.

Keith W Rowe

Ximin Zhang

Sang-hee Lee

Abhishek R Appu

Sang-Hee Lee

Jill MacDonald Boyce

James M Holland

Fangwen Fu

Sumit Mohan

Satya N Yedidi

Joydeep Ray

Ya-Ti Peng

Wen-Fu Kao

Changliang Wang

Scott R Janus

Richmond Hicks

Narayan Biswal

Nausheen Ansari

Nilesh V Shah

Arthur Jeremy Runyan

Robert J Johnston

Gary Smith

Satyanarayana Avadhanam

Altug Koker

Stanley J Baran

Jong Dae Oh

Atthar H Mohammed

Hiu-Fai R Chan

Yi-Jen Chiu

Szu-Wei Lee

Shah Shah

Methods, apparatus, systems, and articles of manufacture are disclosed to improve video encoding. An example apparatus includes at least one memory, instructions, and processor circuitry to at least one of execute or instantiate the instructions to identify a first video frame as a critical video frame with respect to a previous video frame, generate filter coefficients of a video filter based on pixel data of the first video frame or pixel data of a previous critical video frame, and encode the first video frame with the filter coefficients.

Apparatus, articles of manufacture, and methods for improved adaptive loop filtering in video encoding

An example apparatus for encoding video frames includes a mask selector to select a subset of visual masks according to an actual target compression ratio and GOP configuration and a complexity estimator to estimate a picture level spatial/temporal complexity for a current frame. The example apparatus further includes a GOP adaptive visual mask selector to specify a visual mask from the subset of the visual masks corresponding to the estimated spatial and temporal complexity value a good enough picture QP deriver to derive a good enough picture QP value using the visual mask. The example apparatus also includes an adjustor to adjust the good enough picture QP value based on block level human visual system sensitivity and statistics of already encoded frames to obtain a final human visual system QP map.

Human visual system adaptive video coding

Methods, apparatus, systems, and articles of manufacture are disclosed to improve video encoding. An example apparatus includes at least one memory, instructions, and processor circuitry to generate a pool of clipping index set candidates by executing a machine learning model, select a clipping index set from the pool of the clipping index set candidates based on a rate distortion cost associated with the clipping index set, the clipping index set including clipping coefficients, and filter a video frame based on the clipping coefficients.

Apparatus, articles of manufacture, and methods for clipping index identification in adaptive loop filtering for video encoding

Often when there is a glare on a display screen the user may be able to mitigate the glare by tilting or otherwise moving the screen or changing their viewing position. However, when driving a car there are limited options for overcoming glares on the dashboard, especially when you are driving for a long distance in the same direction. Embodiments are directed to eliminating such glare. Other embodiments are related to mixed reality (MR) and filling in occluded areas.

Glare and occluded view compensation for automotive and other applications

Techniques related to adaptive quality boosting for low latency video coding are discussed. Such techniques include segmenting each of a number of temporally adjacent video frames into unique high encode quality regions and encoding each of the video frames by applying a coding quality boost to the high encode quality regions relative to other regions of the video frames.

Adaptive quality boosting for low latency video coding

Techniques related to quantization parameter estimation for coding intra and scene change frames are discussed. Such techniques include generating features based on an intra or scene change frame including a proportion of smooth blocks and one or both of a measure of block variance and a prediction distortion, and applying a machine learning model to generate an estimated quantization parameter for encoding the intra or scene change frame.

Video encoding rate control for intra and scene change frames using machine learning

Techniques related to coding video using adaptive quantization rounding offsets for use in transform coefficient quantization are discussed. Such techniques may include determining the value of a quantization rounding offset for a picture of a video sequence based on evaluating a maximum coding bit limit of the picture, a quantization parameter of the picture, and parameters corresponding to the video.

Content adaptive quantization for video coding

An example apparatus for encoding video frames includes a frame analyzer to execute a look ahead analysis on a received set of frames. The frame analyzer includes a look ahead video analyzer to down-sample the set of frames and encode the down-sampled frames with a constant quantization parameter (QP). A number of generated bits for each of the frames is used as a complexity measurement for each of the frames. The apparatus further includes an encoder to encode the input frame using an adjusted bit allocation based on a relative complexity of the input frame in relation to a complexity of the set of frames.

Adaptively encoding video frames based on complexity

Techniques related to selecting restoration filter coefficients for 2-dimensional loop restoration filters for super resolution video coding are discussed. Such techniques include upscaling reconstructed video frames along only a first dimension and selecting filter coefficients for portions of the frame by an evaluation that, for each pixel of the portion, uses only pixel values that are aligned with the first dimension. Selection of filter coefficients for the second dimension may be skipped or made using only a subset of available filter coefficients.

Loop restoration filtering for super resolution video coding

An embodiment of an electronic processing system may include an application processor, persistent storage media communicatively coupled to the application processor, a graphics subsystem communicatively coupled to the application processor, a power budget analyzer to identify a power budget for one or more of the application processor, the persistent storage media, and the graphics subsystem, a target analyzer communicatively coupled to the graphics subsystem to identify a target for the graphics subsystem, and a parameter adjuster to adjust one or more parameters of the graphics subsystem based on one or more of the identified power budget and the identified target.

Power-based and target-based graphics quality adjustment

An embodiment of an electronic processing system may include a 2D frame which corresponds to a projection of a 360 video space, and a component predictor to predict an encode component for a first block of a 2D frame based on encode information from a neighboring block which is neighboring to the first block of the 2D frame only in the 360 video space, a prioritizer to prioritize transmission for a second block of the 2D frame based on an identified region of interest, and/or a format detector to detect a 360 video format of the 2D frame based on image content. A 360 video capture device may include a contextual tagger to tag 360 video content with contextual information which is contemporaneous with the captured 360 video content. Other embodiments are disclosed and claimed.

MV/mode prediction, ROI-based transmit, metadata capture, and format detection for 360 video

Growing community of inventors

Shingle Springs, CA, United States of America

Keith W Rowe