Qualcomm Incorporated

Vid Scale, Inc.

Interdigital Vc Holdings, Inc.

Louis Joseph Kerofsky

Marta Karczewicz

Geert Van Der Auwera

Bappaditya Ray

Adarsh Krishnan Ramasubramonian

Ralph Neff

Yan Ye

Liangping Ma

Gregory S Sternberg

Kiran Misra

Christopher A Segall

Yuwen He

Anantharaman Balasubramanian

Yuriy Reznik

Seppo T Valli

Pekka K Siltanen

Muhammed Zeyd Coban

Yong He

Dmytro Rusanovskyy

Luong Pham Van

Eduardo Asbun

Rahul Vanam

David Wyble

Alberto Rico Alvarino

Ghyslain Pelletier

Vadim Seregin

Umesh Phuyal

Robert L Olesen

Ariela Zeira

Thomas Stockhammer

Min Wang

Samian Kaur

Dimitrios Karampatsis

Leena Zacharias

Nikolai Konrad Leung

Imed Bouazizi

Robert A DiFazio

Arash Vosoughi

Hilmi Enes Egilmez

Tatu V J Harviainen

Weimin Liu

Zhifeng Chen

Deepankar Katyal

Bing Han

Mikko Juhani Palatsi

Kuan-Ting Shen

Dangdang Shao

Khalid Tahboub

Michael Stefanick

A video coder may code a sign prediction syntax element that indicates whether a sign prediction hypothesis is correct for a transform coefficient. The video coder may code the sign prediction syntax element using a context-based coding process. The video coder may determine a context for coding the sign prediction syntax element based on a position of the transform coefficient in the block of video data. The context may be further based on a coding mode used to code the block.

Context modeling for sign prediction for video coding

Some embodiments of a method may include: identifying two-dimensional (2D) content present in an image of a real-world scene; retrieving metadata comprising depth information associated with the 2D content; generating a plurality of focal plane images using the metadata, the plurality of focal plane images comprising depth cues for the 2D content; and displaying the plurality of focal plane images as a see-through overlay synchronized with the 2D content.

Method and system for near-eye focal plane overlays for 3D perception of content on 2D displays

A method comprises obtaining a first laser angle; obtaining a second laser angle; obtaining a laser angle difference for a third laser angle; determining a predicted value based on the first laser angle and the second laser angle; and determining the third laser angle based on the predicted value and the laser angle difference for the third laser angle.

Coding of laser angles for angular and azimuthal modes in geometry-based point cloud compression

A device for decoding video data receives encoded video data encoded at a first bit-depth; receives in an encoded video bitstream for the video data one or more syntax elements; determines a dequantization shift and a mid-transform shift based on the one or more syntax elements; and performs an inverse transform of the encoded video data at a second bit-depth using the dequantization shift and the mid-transform shift to determine residual values for a block of video data, wherein the second bit-depth is different than the first bit-depth.

Reduced complexity transforms for high bitdepth video coding

A method of decoding point cloud data comprises obtaining a bitstream that is encoded to comply with one or more constraints and decoding the bitstream, wherein decoding the bitstream comprises: determining a residual value of a first component of an attribute of a point; generating a predicted value of a second component of the attribute of the point; and reconstructing the second component as a sum of the predicted value of the second component and a multiplication product of a scale factor for the second component and the residual value of the first component, wherein the constraints include a constraint that limits the first component of the attribute of the point, the residual value of the first component of the attribute of the point, the second component of the attribute, and the residual value of the second component of the attribute of the point to one or more predefined bitdepths.

Residual coding for geometry point cloud compression

Systems, methods, and instrumentalities are disclosed for dynamic picture-in-picture (PIP) by a client. The client may reside on any device. The client may receive video content from a server, and identify an object within the video content using at least one of object recognition or metadata. The metadata may include information that indicates a location of an object within a frame of the video content. The client may receive a selection of the object by a user, and determine positional data of the object across frames of the video content using at least one of object recognition or metadata. The client may display an enlarged and time-delayed version of the object within a PIP window across the frames of the video content. Alternatively or additionally, the location of the PIP window within each frame may be fixed or may be based on the location of the object within each frame.

Tracked video zooming

Certain aspects of the present disclosure provide techniques for global motion modeling. Embodiments include receiving a first image and a second image from a camera attached to a moving object. Embodiments include identifying a pixel in the first image. Embodiments include determining, based on one or more parameters associated with the camera, a vector representing a range of locations in which a real-world point corresponding to the pixel is likely to be found in the second image, wherein the parameters associated with the camera comprise: a first parameter related to a location of the camera relative to a ground surface; a second parameter related to motion of the moving object; and a third parameter related to an orientation of the camera relative to the ground surface. Embodiments include determining, using the vector, a location of the real-world point in the second image.

Global motion modeling for automotive image data

An example method of encoding a point cloud includes determining that residual values for all components except one component of an attribute of a point in the point cloud are equal to zero; based on the determination that the residual values for all components except the one component of the attribute are equal to zero, determining a value for the one component that is equal to a magnitude of a residual value of the one component of the attribute minus an offset; encoding the value of the one component; and signaling the encoded value in a bitstream.

Attribute residual coding in G-PCC

Various embodiments may provide methods, systems, and devices for supporting application level discovery of Radio Access Network (RAN) statistics and/or events. Various embodiments may provide methods, systems, and devices for supporting application level signaling of Quality of Service (QoS) requirements.

Interface between a radio access network and an application

An example method of encoding a point cloud includes determining one or more attribute parameters of an attribute of a point in the point cloud of a frame, wherein the one or more attribute parameters define how to determine or use a value of the attribute and are applicable to a plurality of points in the point cloud; and signaling, in a bitstream indicative of the point cloud, the one or more attribute parameters in a syntax structure that is specific to the frame.

Attribute parameter coding for geometry-based point cloud compression

An example device for decoding point cloud data includes: a memory configured to store point cloud data; and one or more processors implemented in circuitry and configured to: decode a frame of the point cloud data including a plurality of points, each of the points being associated with position values defining a respective position of the point; determine a global scaling factor for the frame; and scale the position values of each of the points by the global scaling factor. The scaling may be clipped to prevent the points exceeding the boundaries of a corresponding bounding box including respective points.

Global scaling for geometry-based point cloud coding

Systems and methods are described for improved color rendering. In some embodiments, video is captured of a real-world scene, and a region of screen content is detected in the captured video. A processor selectively applies a screen-content color transformation on the region of screen content to generate processed video, and the processed video is displayed substantially in real time, for example on a video-see-through head-mounted display. The screen-content color processing may be different for different types of external displays. The screen-content color processing may also be determined based at least in part on illumination conditions. In some embodiments, the color of displayed virtual objects is adjusted based on visual parameters of the screen content.

Method for rendering of augmented reality content in combination with external display

Systems and methods are described for compressing color information in point cloud data. In some embodiments, point cloud data includes point position information and point color information for each of a plurality of points. The point position information is provided to a neural network, and the neural network generates predicted color information (e.g. predicted luma and chroma values) for respective points in the point cloud. A prediction residual is generated to represent the difference between the predicted color information and the input point color position. The point position information (which may be in compressed form) and the prediction residual are encoded in a bitstream. In some embodiments, color hint data is encoded to improve color prediction.

System and method for procedurally colorizing spatial data

Growing community of inventors

San Diego, CA, United States of America

Louis Joseph Kerofsky