Adobe, Inc.

Exfo Solutions Sas

Gwendal Simon

Viswanathan Swaminathan

Stefano Petrangeli

Nathan Aaron Carr

Maha Mdini

Alberto Blanc

Julien Lecoeuvre

Haoliang Wang

Na Wang

The present disclosure relates to systems, methods, and non-transitory computer-readable media to enhance texture image delivery and processing at a client device. For example, the disclosed systems can utilize a server-side compression combination that includes, in sequential order, a first compression pass, a decompression pass, and a second compression pass. By applying this compression combination to a texture image at the server-side, the disclosed systems can leverage both GPU-friendly and network-friendly image formats. For example, at a client device, the disclosed system can instruct the client device to execute a combination of decompression-compression passes on a GPU-network-friendly image delivered over a network connection to the client device. In so doing, client device can generate a tri-pass-compressed-texture from a decompressed image comprising texels with color palettes based on previously reduced color palettes from the first compression pass at the server-side, which reduces computational overhead and increases performance speed.

Generating multi-pass-compressed-texture images for fast delivery

An embodiment may involve: (i) obtaining a set of data records that include respective pluralities of tuples characterizing operation of communication sessions in a network and that identify hardware or software components related to the network that were involved in the communication sessions, (ii) determining degrees to which signatures in the pluralities of tuples are associated with communication problems in the network; (iii) identifying, from the degrees, a subset of the signatures most associated with the communication problems; (iv) grouping specific pairs from the subset of the signatures into equivalence classes based on co-occurrence of signatures of the specific pairs within the data records; (v) generating and pruning a dependency graph between the equivalence classes; (vi) from the equivalence classes remaining in the dependency graph, selecting a subset of the hardware or software components related to the network that are candidates for involvement with the communication problems.

Automatic root cause diagnosis in networks

Techniques and systems are provided for generating a video from texture images, and for reconstructing the texture images from the video. For example, a texture image can be divided into a number of tiles, and the number of tiles can be sorted into a sequence of ordered tiles. The sequence of ordered tiles can be provided to a video coder for generating a coded video. The number of tiles can be encoded based on the sequence of ordered tiles. The encoded video including the encoded sequence of ordered tiles can be decoded. At least a portion of the decoded video can include the number of tiles sorted into a sequence of ordered tiles. A data file associated with at least the portion of the decoded video can be used to reconstruct the texture image using the tiles.

Generation of a sequence of textures for video delivery

The present disclosure relates to systems, non-transitory computer-readable media, and methods that iteratively select versions of augmented reality objects at augmented reality levels of detail to provide for download to a client device to reduce start-up latency associated with providing a requested augmented reality scene. In particular, in one or more embodiments, the disclosed systems determine utility and priority metrics associated with versions of augmented reality objects associated with a requested augmented reality scene. The disclosed systems utilize the determined metrics to select versions of augmented reality objects that are likely to be viewed by the client device and improve the quality of the augmented reality scene as the client device moves through the augmented reality scene. In at least one embodiment, the disclosed systems iteratively select versions of augmented reality objects at various levels of detail until the augmented reality scene is fully downloaded.

Growing community of inventors

Rennes, France

Gwendal Simon