Ati Technologies Ulc

Advanced Micro Devices Corporation

Ihab Amer

Gabor Sines

Yang Liu

Haibo Liu

Edward A Harold

Lei Zhang

Feng Pan

Wei Gao

Khaled Mammou

Boris Ivanovic

Ying Luo

Crystal Yeong-Pian Sau

Ho Hin Lau

Crystal Sau

Fabio Gulino

Guennadi Riguer

Dong Liu

Jinbo Qiu

Michael L Schmit

Mehdi Saeedi

Daniel Wong

Andy Sung

Mingkai Shao

Baochun Li

Shu-Hsien Wu

Kyle Plumadore

Zhiqi Hao

Ehsan Mirhadi

Samuel D Naffziger

David I Glen

Skyler Jonathon Saleh

Ruijin Wu

Zhen Biao Chen

Arun Sundaresan Iyer

Alexander S Duenas

Jiao Wang

Layla A Mah

Ahmed M Abdelkhalek

Omer Irshad

Mohammad Hamed Mousazadeh

Ian Charles Colbert

Zhong Hai Cai

Sonu Thomas

Thomas D Perry

Stephen Ho

Catalin Beju

Tomasz Stolarczyk

Kai Sun

Yuefeng Lu

Lawrence A Bair

Marvin Younan

Minghao Zhu

Stephen Jiacheng Fu

Methods and apparatus encode image frames using intra-frame prediction by predicting pixels for a block of current pixels, based on a detected spatial pattern of pixel intensity differences among a plurality of neighboring reconstructed pixels to the block of current pixels, and encode a block of pixels of the image frame using the predicted block of reconstructed pixels. Inter-frame prediction is provided by determining whether blocks of pixels in temporally neighboring reconstructed frames corresponding to a candidate motion vector have a pattern of pixel intensity differences among the blocks from temporally neighboring frames. Predicted blocks are produced for a reconstructed frame based on the determined pattern of pixel intensity difference among temporally neighboring frames.

Video encoding/decoding using detected pattern of pixel intensity differences

Adaptive digital content preprocessing techniques based on a bitrate are described. In an implementation, a parameter of a preprocessing module is set based on a target bitrate. The parameter specifies an amount of preprocessing to be performed in preprocessing digital content. Preprocessed digital content is generated by preprocessing the digital content by the specified amount using the preprocessing module. Encoded digital content is generated by compressing the preprocessed digital content using a compression technique by an encoder. The encoded digital content is then transmitted for communication at the target bitrate.

Adaptive digital content preprocessing based on bitrate

To leverage an amount of unused bandwidth at a hardware encoder to generate motion estimation data, a processing unit includes a hardware encoder configured to perform a first encoding job including encoder sessions to encode a captured frame, determine motion estimation data for a rendered frame, and encode the rendered frame. Further, the processing unit includes a pre-processing circuitry configured to determine a set of motion estimation parameters based on an encoder delay associated with the performance of the first encoding job by the hardware encoder. The hardware encoder is then configured to perform a second encoding job using the determined set of motion estimation parameters.

Dynamic motion estimation parameter modification for video encoding

A processing device includes an automated overclocking system and a processor. The automated overclocking system is data-driven and includes an inference engine that executes a machine learning model configured to generate a first output based on a current configuration of the processing device. The first output includes a first set of overclocking parameters. The processor is configured to adjust one or more operating characteristics of at least one component of the processing device based on the first set of overclocking parameters.

Automated data-driven system to optimize overclocking

An encoder encodes an image portion by recursively partitioning the portion into a partitioning hierarchy of levels. The top level has a single block representing the entire portion and each lower level has four smaller blocks representing a corresponding larger block at a higher level. A palette table is generated for each bottom-level block based on the pixels of the associated block. For each successively higher level, the encoder generates a palette table for each current-level block by selecting palette colors based on the palette colors from the four palette tables for the associated four blocks at the next-lowest level. A color index map is then generated based on a final palette table selected from the palette tables generated for the partitioning hierarchy. A representation of the portion is then encoded using the final palette table and the color index map to generate a corresponding segment of an encoded bitstream.

Palette mode video encoding utilizing hierarchical palette table generation

Systems, apparatuses, and methods for performing parallel histogram calculation with application to palette table derivation are disclosed. An encoder calculates a first histogram for a first portion of pixel component value bits of a block of pixels. Then, the encoder selects a first number of the highest pixel count bins from the first histogram. Also, the encoder calculates a second histogram for a second portion of pixel component value bits of the block. The encoder selects a second number of the highest pixel count bins from the second histogram. A third histogram is calculated from the concatenation of bits assigned to the first and second number of bins, and the highest pixel count bins are selected from the third histogram. A palette table is derived based on these highest pixel count bins selected from the third histogram, and the block of pixels is encoded using the palette table.

Parallel histogram calculation with application to palette table derivation

Systems, apparatuses, and methods for calculating multi-pass histograms for palette table derivation are disclosed. An encoder calculates a first histogram for a first portion of most significant bits (MSBs) of pixel component values of a block of an image or video frame. Then, the encoder selects a given number of the highest pixel count bins from the first histogram. The encoder then increases the granularity of these selected highest pixel count bins by evaluating one or more additional bits from the pixel component values. A second histogram is calculated for the concatenation of the original first portion MSBs from the highest pixel count bins and the one or more additional bits, and the highest pixel count bins are selected from the second histogram. A palette table is derived based on these highest pixel count bins selected from the second histogram, and the block is encoded using the palette table.

Hierarchical histogram calculation with application to palette table derivation

A feedback processing module includes a memory configured to store feedback received from an encoder. The feedback includes parameters associated with encoded graphics content generated by a graphics engine. The feedback processing module also includes a processor configured to generate configuration information for the graphics engine based on the feedback. The graphics engine is configured to execute a workload based on the configuration information. In some cases, the feedback processing module is also configured to receive feedback from a decoder that is used to decode the graphics content that is encoded by the encoder and generate the configuration information based on the feedback received from the decoder.

Graphics rendering with encoder feedback

Reference frame detection using sensor metadata, including: storing a plurality of first frames each corresponding to first metadata, wherein the first metadata for each first frame of the plurality of first frames is based on first sensor data from one or more sensors; generating a second frame corresponding to second metadata based on the one or more sensors; identifying, based on the first metadata of the plurality of first frames and the second metadata, a reference frame of the plurality of first frames; and encoding the second frame based on the reference frame.

Reference frame detection using sensor metadata

A server offloads graphics effects processing to a client device with graphics processing resources by determining a modification to a graphics effects operation, generating a portion of a rendered video stream using the modification to the graphics effects operation, and providing an encoded representation of the portion of the rendered video stream to the client device, along with metadata representing the modification implemented. The client device decodes the encoded representation to recover the portion of the rendered video stream and selectively performs a graphics effects operation on the recovered portion to at least partially revert the resulting graphics effects for the portion to the intended effects without the modification implemented by the server.

Client-side offload of graphics effects processing

Calculating, for each frame of a plurality of frames, a corresponding quality value; calculating, for each frame of the plurality of frames, based on one or more visual attributes of a frame, a weight for the corresponding quality value of the frame; calculating an aggregate quality value for the plurality of frames based on the weight and the corresponding quality value for each frame of the plurality of frames; and providing an assessment of the plurality of frames based on the aggregate quality value for the plurality of frames.

Video quality assessment using aggregated quality values

Methods and apparatus provide cloud-based video encoding that generates encoded video data by one or more encoders in a cloud platform for a plurality of cloud encoding sessions. The methods and apparatus generate operational improvement tradeoff data in response to operational encoding metrics associated with the one or more encoders and change operational characteristics of the one or more encoders for at least one of the cloud encoding sessions based on the operational improvement tradeoff data.

Method and apparatus for providing cloud-based video encoding

Systems, apparatuses, and methods for generating a model for determining a quantization strength to use when encoding video frames are disclosed. A pre-encoder performs multiple encoding passes using different quantization strengths on a portion or the entirety of one or more pre-processed video frames. The pre-encoder captures the bit-size of the encoded output for each of the multiple encoding passes. Then, based on the multiple encoding passes, the pre-encoder generates a model for mapping bit-size to quantization strength for encoding video frames or portion(s) thereof. When the encoder begins the final encoding pass for one or more given video frames or any portion(s) thereof, the encoder uses the model to map a preferred bit-size to a given quantization strength. The encoder uses the given quantization strength when encoding the given video frame(s) or frame portion(s) to meet a specified bit-rate for the encoded bitstream.

Content adaptive quantization strength and bitrate modeling

The present disclosure is directed a system and method for exploiting camera and depth information associated with rendered video frames, such as those rendered by a server operating as part of a cloud gaming service, to more efficiently encode the rendered video frames for transmission over a network. The method and system of the present disclosure can be used in a server operating in a cloud gaming service to improve, for example, the amount of latency, downstream bandwidth, and/or computational processing power associated with playing a video game over its service. The method and system of the present disclosure can be further used in other applications where camera and depth information of a rendered or captured video frame is available.

Exploiting camera depth information for video encoding

Growing community of inventors

Markham, Canada

Ihab Amer