Abstract: A method, system and computer-usable medium for using cognitive graph vectors to refine cognitive insights comprising storing data from a plurality of data sources within a cognitive graph via a cognitive inference and learning system; associating a first set of the data within the cognitive graph with a first cognitive graph vector of a plurality of cognitive graph vectors via the cognitive inference and learning system; associating a second set of the data within the cognitive graph with a second cognitive graph vector of the plurality of cognitive graph vectors via the cognitive inference and learning system; processing the data from the plurality of data sources to provide cognitive insights via the cognitive inference and learning system; and refining the cognitive insights based upon a limitation relating to one of the plurality of cognitive graph vectors via the cognitive inference and learning system.

Abstract: A video block of a current picture may be coded in an intra block copy (IBC) mode. Weighted prediction may be disabled for the IBC-coded screen content video block. Fractional block vectors may be used for the chroma components of the IBC-coded video block. An interpolation filter may be utilized to generate chroma prediction samples for the video block. A decoded version of the current reference picture may be added to both reference picture list L0 and reference picture list L1 that are associated with the IBC-coded video block. When constrained intra prediction is applied, reference samples that may be used to predict an intra-coded video block may be limited to those in intra-coded neighboring blocks. The range of IBC searches may be restricted by imposing a maximum absolute value for block vectors.

Abstract: Systems, methods, and instrumentalities are provided to implement video coding system (VCS). The VCS may be configured to receive a video signal, which may include one or more layers (e.g., a base layer (BL) and/or one or more enhancement layers (ELs)). The VCS may be configured to process a BL picture into an inter-layer reference (ILR) picture, e.g., using picture level inter-layer prediction process. The VCS may be configured to select one or both of the processed ILR picture or an enhancement layer (EL) reference picture. The selected reference picture(s) may comprise one of the EL reference picture, or the ILR picture. The VCS may be configured to predict a current EL picture using one or more of the selected ILR picture or the EL reference picture. The VCS may be configured to store the processed ILR picture in an EL decoded picture buffer (DPB).

Abstract: A video encoding device (e.g., a wireless transmit/receive unit (WTRU)) may transmit an encoded frame with a frame sequence number using a transmission protocol. The video encoding device, an application on the video encoding device, and/or a protocol layer on the encoding device may detect a packet loss by receiving an error notification. The packet loss may be detected at the MAC layer. The packet loss may be signaled using spoofed packets, such as a spoofed NACK packet, a spoofed XR packet, or a spoofed ACK packet. A lost packet may be retransmitted at the MAC layer (e.g., by the encoding device or another device on the wireless path). Packet loss detection may be performed in uplink operations and/or downlink operations, and/or may be performed in video gaining applications via the cloud. The video encoding device may generate and send a second encoded frame based on the error notification.

Abstract: A cognitive information processing system comprising: a cognitive inference and learning system coupled to receive data from a plurality of data sources and to provide insights to a destination, the cognitive inference and learning system comprising a first interface, the first interface providing the data from the plurality of data sources to the cognitive interface and learning system, and, the cognitive inference and learning system comprising a second interface, the second interface providing the cognitively processed insights to the destination.

Abstract: Described herein are methods and systems associated with viewing condition adaption of multimedia content. A method for receiving multimedia content with a device from a network may include determining a viewing parameter, transmitting a request for the multimedia content to the network, whereby the request may be based on the viewing parameter, and receiving the multimedia content from the network, whereby the multimedia content may be processed at a rate according to the viewing parameter. The viewing parameter may include at least one of: a user viewing parameter, a device viewing parameter, or a content viewing parameter. The method may further include receiving a multimedia presentation description (MPD) file from the network. The MPD file may include information relating to the rate of the multimedia content and information relating to the rate may include a descriptor relating to the viewing parameter, whereby the descriptor may be required or optional.

Abstract: Systems, methods, and instrumentalities are disclosed for enhancing performance of multi-path communications. Multi-path communication performance may be enhanced by determining whether multipath communications share a congested router. A multi-path real-time communication protocol may provide techniques to prevent, detect, communicate and respond to a shared congested router. A shared congested router may be prevented, and/or detected using one or more detection techniques.

Abstract: A data architecture for use within a cognitive information processing system environment comprising: a plurality of data sources, the plurality of data sources comprising a public data source and a private data source, the public data source comprising publicly available healthcare information, the private data source comprising privately managed, company specific healthcare information; and, a cognitive data management module, the cognitive data management module accessing information from the plurality of data sources and providing the information to an inference and learning system.

Abstract: Systems, methods, and instrumentalities for sub-block motion derivation and motion vector refinement for merge mode may be disclosed herein. Video data may be coded (e.g., encoded and/or decoded). A collocated picture for a current slice of the video data may be identified. The current slice may include one or more coding units (CUs). One or more neighboring CUs may be identified for a current CU. A neighboring CU (e.g., each neighboring CU) may correspond to a reference picture. A (e.g., one) neighboring CU may be selected to be a candidate neighboring CU based on the reference pictures and the collocated picture. A motion vector (MV) (e.g., collocated MV) may be identified from the collocated picture based on an MV (e.g., a reference MV) of the candidate neighboring CU. The current CU may be coded (e.g., encoded and/or decoded) using the collocated MV.

Abstract: External overlapped block motion compensation (OBMC) may be performed for samples of a coding unit (CU) located along an inter-CU boundary of the CU while internal OBMC may be performed separately for samples located along inter-sub-block boundaries inside the CU. External OBMC may be applied based on substantially similar motion information associated with multiple external blocks neighboring the CU. The external blocks may be treated as a group to provide OBMC for multiple boundary samples together in an external OBMC operation. Internal OBMC may be applied using the same sub-block size used for sub-block level motion derivation. Internal OBMC may be disabled for the CU, for example, if the CU is coded in a spatial-temporal motion vector prediction (STMVP) mode.

Abstract: Methods and systems are disclosed for a mobile device to decode video based on available power and/or energy. For example, the mobile device may receive a media description file (MDF) from for a video stream from a video server. The MDF may include complexity information associated with a plurality of video segments. The complexity information may be related to the amount of processing power to be utilized for decoding the segment at the mobile device. The mobile device may determine at least one power metric for the mobile device. The mobile device may determine a first complexity level to be requested for a first video segment based on the complexity information from the MDF and the power metric. The mobile device may dynamically alter the decoding process to save energy based on the detected power/energy level.

Abstract: Video data, e.g., screen content video data may be palette coded. A palette table including one or more color indices may be produced. A color index may correspond to one color. A palette index map may be created that maps one or more pixels of the video data to a color index in the palette table, or a color that may be explicitly coded. A palette index map prediction data may be generated that includes data that indicates values in the palette index map associated with at least some portions of the video data that are generated in a traverse scan order in which a scan line is scanned in an opposite direction of a preceding parallel scan line.

Abstract: A system, method, and/or instrumentality may be provided for coding a 360-degree video. A picture of the 360-degree video may be received. The picture may include one or more faces associated with one or more projection formats. A first projection format indication may be received that indicates a first projection format may be associated with a first face. A second projection format indication may be received that indicates a second projection format may be associated with a second face. Based on the first projection format, a first transform function associated with the first face may be determined. Based on the second projection format, a second transform function associated with the second face may be determined. At least one decoding process may be performed on the first face using the first transform function and/or at least one decoding process may be performed on the second face using the second transform function.

Abstract: A method, system and computer-usable medium for performing cognitive computing operations comprising receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph; defining a cognitive persona within the cognitive graph, the cognitive persona corresponding to an archetype user model, the cognitive persona comprising a set of nodes in the cognitive graph, links among the set of nodes being weighted to provide a weighted cognitive graph; associating a user with the cognitive persona; and, performing a cognitive computing operation based upon the cognitive persona associated with the user.

Abstract: A method, system and computer-usable medium for performing cognitive computing operations comprising receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph; defining a cognitive persona within the cognitive graph, the cognitive persona corresponding to an archetype user model, the cognitive persona comprising a set of nodes in the cognitive graph; associating a user with the cognitive persona; defining a cognitive profile within the cognitive graph, the cognitive profile comprising an instance of the cognitive persona that references personal data associated with the user; associating the user with the cognitive profile; and, performing a cognitive computing operation based upon the cognitive profile associated with the user.

Abstract: A method, system and computer readable medium for generating a cognitive insight comprising: receiving information regarding a temporal sequence of events; performing a temporal topic machine learning operation on the temporal sequence of events; generating a cognitive profile based upon the information generated by performing the temporal topic machine learning operation; and, generating a cognitive insight based upon the cognitive profile generated using the temporal topic machine learning operation.

Abstract: Systems, methods, and instrumentalities are disclosed for a 360-degree video streaming. A video streaming device may receive a 360-degree video stream from a network node. The video streaming device may determine a viewport associated with the video streaming device and/or the 360-degree video stream. The video streaming device may determine (e.g., based on the viewport} to request in advance a first segment and a second segment of the 360-degree video stream. The video streaming device may determine a relative priority order for the first segment and the second segment. The video streaming device may generate an anticipated requests message. The anticipated requests message may indicate the determined relative priority order, for example, by listing the first segment and the second segment in decreasing relative priority based on the determined relative priority order. The video streaming device may send the anticipated requests message to the network node.

Abstract: Systems, methods, and instrumentalities are provided to implement video coding system (VCS). The VCS may be configured to receive a video signal, which may include one or more layers (e.g., a base layer (BL) and/or one or more enhancement layers (ELs)). The VCS may be configured to process a BL picture into an inter-layer reference (ILR) picture, e.g., using picture level inter-layer prediction process. The VCS may be configured to select one or both of the processed ILR picture or an enhancement layer (EL) reference picture. The selected reference picture(s) may comprise one of the EL reference picture, or the ILR picture. The VCS may be configured to predict a current EL picture using one or more of the selected ILR picture or the EL reference picture. The VCS may be configured to store the processed ILR picture in an EL decoded picture buffer (DPB).

Abstract: A video block of a current picture may be coded in an intra block copy (IBC) mode. Weighted prediction may be disabled for the IBC-coded screen content video block. Fractional block vectors may be used for the chroma components of the IBC-coded video block. An interpolation filter may be utilized to generate chroma prediction samples for the video block. A decoded version of the current reference picture may be added to both reference picture list L0 and reference picture list L1 that are associated with the IBC-coded video block. When constrained intra prediction is applied, reference samples that may be used to predict an intra-coded video block may be limited to those in intra-coded neighboring blocks. The range of IBC searches may be restricted by imposing a maximum absolute value for block vectors.

Abstract: Processing video data may include capturing the video data with multiple cameras and stitching the video data together to obtain a 360-degree video. A frame-packed picture may be provided based on the captured and stitched video data. A current sample location may be identified in the frame-packed picture. Whether a neighboring sample location is located outside of a content boundary of the frame-packed picture may be determined. When the neighboring sample location is located outside of the content boundary, a padding sample location may be derived based on at least one circular characteristic of the 360-degree video content and the projection geometry. The 360-degree video content may be processed based on the padding sample location.