Abstract: A video generating device obtains Laplace pyramid levels of 360° video frames; upscales each of the obtained Laplace pyramid levels so as to recover a set of corresponding Gaussian pyramid levels for each 360° video frame; determines a recovered Gaussian pyramid level among the set of recovered Gaussian pyramid levels for each pixel in each 360° video frame based on a bitrate budget for live streaming and a viewport region by performing a pyramid level assignment procedure; composes a 360° video with heterogeneous spatial quality based on summing up the determined recovered Gaussian pyramid levels for each pixel in each 360° video frame. Thereby, reduction of bitrate while providing a high video quality to the user when watching 360° videos is possible. Furthermore, the disclosure also relates to a download proxy comprising such a video generating device, corresponding methods, and a computer program.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method for obtaining video chunks of a video sphere for display on a head-mounted display connected to a video server is described, the video chunks being spatially split into a plurality of tiles that can be encoded on at least two different quality levels, including a high quality level and a low quality level, and a display window includes a video sphere portion that is to be displayed at a particular display time. Prior to the display time, the display window is predicted, tiles covering the estimated display window are estimated, and assigned a high quality level, and tiles adjoining those tiles are estimated and assigned a low quality level. A request is sent to a video server to obtain an encoded tile at the associated quality level. The tiles are received from the video server, the display window is determined, and the tiles corresponding to the determined display window are decoded and displayed.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A video generating device obtains Laplace pyramid levels of 360° video frames; upscales each of the obtained Laplace pyramid levels so as to recover a set of corresponding Gaussian pyramid levels for each 360° video frame; determines a recovered Gaussian pyramid level among the set of recovered Gaussian pyramid levels for each pixel in each 360° video frame based on a bitrate budget for live streaming and a viewport region by performing a pyramid level assignment procedure; composes a 360° video with heterogeneous spatial quality based on summing up the determined recovered Gaussian pyramid levels for each pixel in each 360° video frame. Thereby, reduction of bitrate while providing a high video quality to the user when watching 360° videos is possible. Furthermore, the disclosure also relates to a download proxy comprising such a video generating device, corresponding methods, and a computer program.

Abstract: 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.

Abstract: 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.

Abstract: A method for obtaining video chunks of a video sphere for display on a head-mounted display connected to a video server is described, the video chunks being spatially split into a plurality of tiles that can be encoded on at least two different quality levels, including a high quality level and a low quality level, and a display window includes a video sphere portion that is to be displayed at a particular display time. Prior to the display time, the display window is predicted, tiles covering the estimated display window are estimated, and assigned a high quality level, and tiles adjoining those tiles are estimated and assigned a low quality level. A request is sent to a video server to obtain an encoded tile at the associated quality level. The tiles are received from the video server, the display window is determined, and the tiles corresponding to the determined display window are decoded and displayed.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A content distribution network has at least two network stations adapted for storing and retrieving content. Content is divided in fragments scattered across different network stations. When a further network station is added to the network it determines which fragments of a desired content are available from other network stations within a predetermined maximum distance. In case not all fragments of the desired content are available from other network stations within the predetermined maximum distance the added network station downloads a random fragment from a set of missing fragments of the desired content from a network station that is further away than the predetermined maximum distance. Otherwise the added network station determines a set of network stations located within the predetermined maximum distance having the closest distance to the added network station, while, in their totality, making available all fragments of the desired content required for reconstructing the complete file.

Abstract: Entities of a wireless communication network adjacent to a given sending entity, i.e. entities of the network from which the sending entity is able to receive messages are identified. Among the adjacent entities, a minimum constellation associated with the sending entity is further identified as the smallest set of entities adjacent to the sending entity and included in a circle centered on the sending entity such that at least three of the entities of the set form a convex polygon circumscribing the sending entity. The transmitting power of the sending entity is then adjusted to a value sufficient for the messages sent by the sending entity to reach all the entities of the minimum constellation associated therewith.

Abstract: Entities of a wireless communication network adjacent to a given sending entity, i.e. entities of the network from which the sending entity is able to receive messages are identified. Among the adjacent entities, a minimum constellation associated with the sending entity is further identified as the smallest set of entities adjacent to the sending entity and included in a circle centered on the sending entity such that at least three of the entities of the set form a convex polygon circumscribing the sending entity. The transmitting power of the sending entity is then adjusted to a value sufficient for the messages sent by the sending entity to reach all the entities of the minimum constellation associated therewith.