Intel Corporation

Thomson Licensing

Hitachi America, Ltd.

Vidyo, Inc.

Lucent Technologies Inc.

Interdigital Vc Holdings, Inc.

Hitachi, Ltd.

Interdigital Madison Patent Holdings

Vimmerse, Inc.

At+t Corp.

Thomson Licensing S.a.

Matsushita Electric Corporation of America

Thomson Research Funding Corporation

Dolby International Ab

Thomson Licensing Dtv

Jill MacDonald Boyce

Peng Yin

Alexandros Michael Tourapis

Larry Alan Pearlstein

Frank Anton Lane

Prasoonkumar Surti

Sumit Mohan

Purvin Bibhas Pandit

Stanley J Baran

Jeffrey Allen Cooper

Danny Hong

James M Holland

Basel Salahieh

Abhishek R Appu

Kumar Ramaswamy

Scott R Janus

Jason Daniel Tanner

Michael Allen Plotnick

Michael Apodaca

Adam T Lake

Cristina Gomila

Barnan Das

Archie Sharma

Fangwen Fu

Joseph Ellis Augenbraun

Yi-Jen Chiu

Narayan Biswal

Joan Llach

Jong Dae Oh

John G Henderson

Atthar H Mohammed

Altug Koker

Stephan Wenger

Sang-Hee Lee

Gokcen Cilingir

Keith W Rowe

Satya N Yedidi

Srikanth Potluri

Lidong Xu

Atsuo Kuwahara

Richmond Hicks

Karthik Veeramani

Hugues Labbe

Masuo Oku

Jack S Fuhrer

Varghese George

Carl S Marshall

Changliang Wang

Deepak Shashidhar Vembar

Selvakumar Panneer

Zhenyu Wu

Nilesh V Shah

Mayuresh M Varerkar

Hiu-Fai R Chan

Zhijun Lei

Jeffrey Tripp

Joydeep Ray

Subramaniam M Maiyuran

Vasanth Ranganathan

Hiroo Okamoto

Nikos Kaburlasos

Kai Xiao

Xiaoan Lu

Takaharu Noguchi

Masafumi Nakamura

Katsuo Mohri

Tzach Ashkenazi

Glen J Anderson

Vallabhajosyula S Somayazulu

Mike MacPherson

Nilesh K Jain

Sherine Abdelhak

Zhengmin Li

Rajesh Poornachandran

Christopher J Hughes

Guei-Yuan Lueh

Yao Rong Wang

Ximin Zhang

Fai Yeung

Sang-hee Lee

Ya-Ti Peng

Yunbiao Lin

Robert J Johnston

Hua Yang

Soethiha Soe

Jonathan Michael Lennox

David Anthony Campana

Satyanarayana Avadhanam

Maria Bortman

Kshitij Arun Doshi

Zhipin Deng

Yeping Su

Giuseppe Beppe Raffa

Ignacio Javier Alvarez

Hang Liu

Sean J Lawrence

Rajneesh Chowdhury

Brinda Ganesh

David Gray Boyer

Ankur Agrawal

Disclosed examples include video frame segmenter circuitry to generate segmentation data of first video frame pixel data, the segmentation data including metadata corresponding to a foreground region and a background region, the foreground region corresponding to the first video frame pixel data. The disclosed examples also include video encoder circuitry to generate a first foreground bounding region and a first background bounding region based on the segmentation data, determine a first virtual tile of the first video frame pixel data, the first virtual tile located in the first foreground bounding region, encode the first virtual tile into a video data bitstream without encoding the first background bounding region, and transmit the video data bitstream via a network.

Methods and apparatus to process video frame pixel data using artificial intelligence video frame segmentation

Methods, apparatus, systems and articles of manufacture to identify a video decoding error are disclosed. An example apparatus includes an atlas generator to generate atlas data for one or more atlases generated from input views of video; a hash generator to: perform a hash operation on the atlas data to generate a hash value; and include the hash value in a message; and a multiplexer to combine the one or more atlases, coded atlas data corresponding to the atlas data, and the message to generate a video bitstream.

Methods and apparatus to identify a video decoding error

Example methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement multi-plane image (MPI) compression are disclosed. Example apparatus disclosed herein include an interface to access an input multiplane image stack corresponding to a source camera viewpoint, the input multiplane image stack including a plurality of texture images and a corresponding plurality of alpha images, ones of the alpha images including pixel values representative of transparency of corresponding pixels in respective ones of the texture images. Disclosed example apparatus also include a compressed image encoder to at least one of (i) convert the plurality of texture images to a single composite texture image to generate a compressed multiplane image stack, or (ii) convert the plurality of alpha images to a single composite alpha image to generate the compressed multiplane image stack. In some disclosed examples, the interface is to output the compressed multiplane image stack.

Multi-plane image compression

A mechanism is described for facilitating adaptive resolution and viewpoint-prediction for immersive media in computing environments. An apparatus of embodiments, as described herein, includes one or more processors to receive viewing positions associated with a user with respect to a display, and analyze relevance of media contents based on the viewing positions, where the media content includes immersive videos of scenes captured by one or more cameras. The one or more processors are further to predict portions of the media contents as relevant portions based on the viewing positions and transmit the relevant portions to be rendered and displayed.

Adaptive resolution of point cloud and viewpoint prediction for video streaming in computing environments

Methods, apparatus, systems and articles of manufacture to generate packed video frames are disclosed. A video encoding system disclosed herein includes a configuration determiner to create a packed video frame layout that includes regions into which video components are to be placed. The system also includes a frame generator to form packed video frames that include the video components placed into different regions. The encoding system further includes a frame information generator that generates packed video frame information that identifies characteristics of the packed video frame including (i) the identities of regions included in the packed video frame layout, (ii) types of video components included in the regions, or iii) information identifying the locations and dimensions of the regions. A video encoder of the encoding system encodes the frames and includes the packed video frame information to signal the inclusion of the packed video frames in the encoded bitstream.

Method, apparatus, and articles of manufacture to generate packed video frames for a volumetric video bitstream and an immersive video bitstream

Devices and techniques related to implementing patch based video coding for machines are discussed. Such patch based video coding includes detecting regions of interest in a frame of video, extracting the detected regions of interest to one or more atlases absent the frame at a resolution not less than the resolution of the regions of interest, and encoding the one or more atlases to a bitstream.

Patch based video coding for machines

Embodiments described herein provided for an instruction and associated logic to enable a processing resource including a tensor accelerator to perform optimized computation of sparse submatrix operations. One embodiment provides a parallel processor comprising a processing cluster coupled with the cache memory. The processing cluster includes a plurality of multiprocessors coupled with a data interconnect, where a multiprocessor of the plurality of multiprocessors includes a tensor core configured to load tensor data and metadata associated with the tensor data from the cache memory, wherein the metadata indicates a first numerical transform applied to the tensor data, perform an inverse transform of the first numerical transform, perform a tensor operation on the tensor data after the inverse transform is performed, and write output of the tensor operation to a memory coupled with the processing cluster.

Systolic arithmetic on sparse data

Content hosting for composite video is described using metadata and user identification. A user management module registers a first user ID for a primary device, a second user ID for a secondary device, a session ID for a session between the primary device and the secondary device, and a player device with a third user ID and privileges to view a composite video. A content hosting module receives a first video associated with the first user ID and the session ID and a second video associated with the second user ID and the session ID. The first and second videos include metadata regarding time and position. The content hosting module serves a composite video to the player device in response to a request associated with the third user ID. A content preparation module forms the composite video using the first video and the second video.

Collaborative video capture and sharing

Techniques related to immersive video coding are discussed and include immersive video sequences and output units for random access to the immersive video, coding improvements for camera parameters coding, and coding efficiency improvements for atlas parameters.

Immersive video coding techniques for three degree of freedom plus/metadata for immersive video (3DoF+/MIV) and video-point cloud coding (V-PCC)

Methods, apparatus, systems and articles of manufacture to sample enabled views per atlas in immersive video are disclosed. An example apparatus includes an interface to obtain a bitstream corresponding to an immersive video; a bitstream analyzer to determine that metadata corresponding to an atlas of the bitstream identifies that at least part of a view of interest corresponds to the atlas, the metadata included in the bitstream; and a filter to generate a filtered bitstream by removing atlases that do not identify at least part of a view of interest from the bitstream, the interface to provide the filtered bitstream to a decoder.

Methods and apparatus to signal enabled views per atlas in immersive video

One embodiment provides a graphics processor comprising a block of execution resources, a cache memory, a cache memory prefetcher, and circuitry including a programmable neural network unit, the programmable neural network unit comprising a network hardware block including circuitry to perform neural network operations and activation operations for a layer of a neural network, the programmable neural network unit addressable by cores within the block of graphics cores and the neural network hardware block configured to perform operations associated with a neural network configured to determine a prefetch pattern for the cache memory prefetcher.

Graphics architecture including a neural network pipeline

Methods, apparatus, systems and articles of manufacture for object-based volumetric video coding are disclosed. An example apparatus disclosed herein includes a point annotator to receive point cloud data associated with an object and annotate points of the point cloud data with an object identifier of the object. The disclosed example apparatus also includes a projector to project the point cloud data onto projection planes to produce texture images and geometry images. The disclosed example apparatus further includes a patch generator to generate a patch based on the object identifier, the patch including the texture images and the geometry images of the object, the patch associated with the object identifier of the object. The disclosed example apparatus also includes an atlas generator to generate an atlas to include in encoded video data, the atlas including the patch.

Object-based volumetric video coding

A mechanism is described for facilitating defining of interoperability signaling and conformance points for the PCC standard in computing environments. A computing device of embodiments, as described herein, includes a decoder to decode a compressed bitstream of video data representing a point cloud, point cloud reconstructor circuitry to reconstruct a point cloud from the decoded patch video data, a syntax element parser to receive at least one syntax element representing interoperability signaling in the compressed bitstream to indicate the number of points in one or more pictures of the video data, and processing hardware to determine if the number of points in the one or more pictures of the compressed bitstream is within the conformance limits of the point cloud reconstructor circuitry.

Point cloud coding standard conformance definition in computing environments

Embodiments are generally directed to selective packing of patches for immersive video. An embodiment of a processing system includes one or more processor cores; and a memory to store data for immersive video, the data including a plurality of patches for multiple projection directions. The system is select the patches for packing, the selection of the patches based at least in part on which of the multiple projection directions is associated with each of the patches. The system is to encode the patches into one or more coded pictures according to the selection of the patches.

Selective packing of patches for immersive video

An example apparatus for adaptively encoding video frames includes a network analyzer to predict an instant bitrate based on channel throughput feedback received from a network. The apparatus also includes a content analyzer to generate ladder info based on a received frame. The apparatus further includes an adaptive decision executer to determine a frame rate, a video resolution, and a target frame size based on the predicted instant bitrate and the ladder outputs. The apparatus further includes an encoder to encode the frame based on the frame rate, the video resolution, and the target frame size.

Adaptively encoding video frames using content and network analysis

Growing community of inventors

Manalapan, NJ, United States of America

Jill MacDonald Boyce