Qualcomm Incorporated

Vid Scale, Inc.

Brightcove Inc.

Interdigital Patent Holdings, Inc.

Realnetworks Gmbh

Intel Corporation

Qualcom Incorporate

Yuriy Reznik

Gregory S Sternberg

Eduardo Asbun

Liangping Ma

Chong U Lee

John Hyunchul Hong

Marta Karczewicz

Rajan Laxman Joshi

Weimin Liu

Ariela Zeira

Samian Kaur

Anantharaman Balasubramanian

Wei Yu Chen

Hang Liu

Ralph Neff

Harinath Garudadri

Osama Lotfallah

Louis Joseph Kerofsky

Oghenekome Oteri

Yan Ye

Naveen Srinivasamurthy

Stephen E Terry

Wei-Jung Chien

Robert L Olesen

Eldad M Zeira

Alexander Reznik

Joel Sole Rojals

Peisong Chen

Dimitrios Karampatsis

Yong He

Michelle Perras

Murali Chari

Pawan Kumar Baheti

Wei Chen

Onur Canturk Hamsici

Rahul Vanam

Sundeep Vaddadi

Zhifeng Chen

Avi Rapaport

Karl O Lillevold

Justin R Greer

Abhijith Jagannath

Michael Harty

Ravi Kiran Chivukula

Jorge Cenzano Ferret

Ted Krofssik

Matthew Neil

Hyukjune Chung

Albert Scott Ludwin

Phoom Sagetong

Naresh H Soni

Xiangbo Li

Manish Rao

Ashwin Deepak Swaminathan

Hsiao-Chiang Chuang

Pengjun Huang

Devender Akira Yamakawa

Jose Ricardo Dos Santos

Naveen B Srinivasamurthy

Joseph Huang

Dharm Veer

Mark K Murphy

Bo Zhang

Murali Ramaswamy Chari

Chong Uk Lee

Samian J Kaur

Devender A Yamakawa

José R Dos Santos

Techniques described herein are directed toward creating one or more 'dynamic profiles' for media (video) streaming in which an encoding bit rate (and optionally other profile settings) is optimized for particular content. More specifically, techniques involve performing one or more “probe” encodings of the particular content to determine an encoding bit rate (and optionally other profile settings) that results in an encoding having a quality value sufficiently near (within a threshold) a target quality value.

Optimization of encoding profiles for media streaming

A method for creating a low latency DASH (LL-DASH) video stream from a Low latency HLS video stream (LL-HLS) is provided. The LL-HLS video stream corresponding to a live event is retrieved. The LL-HLS video stream is converted to a LL-DASH video stream. This conversion of the LL-DASH stream from the LL-HLS stream provides reformatting without encoding of the LL-DASH stream.

Dynamic creation of low latency video streams in a live event

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.

Methods and systems for video delivery supporting adaptation to viewing conditions

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 NAM 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.

Early packet loss detection and feedback

A fault-tolerant, cloud-based system can comprise a redundancy control unit capable of switching between transcoded video streams output by two or more transcoders. The redundancy control unit outputs a manifest from one of the transcoded streams and, upon detecting a fault in the stream, can modify the manifest to switch to another of the transcoded video streams. The redundancy control unit can further modify the manifest to flag the discontinuity in the video stream, which allows the player to switch to the new transcoding video stream without error. Other embodiments can include additional redundancies to help provide additional fault tolerance.

Fault tolerant live video streaming switchover

Techniques are disclosed for the creation of multi-codec encoding profiles (or encoding ladders), which define quality and bitrate for each of the streams made available to clients for streaming a video. In particular, optimization techniques may take into account a quality rate function of each of the codecs when determining the encoding ladder. Additional considerations may include a network bandwidth distribution and/or a distribution of client types.

Optimal multi-codec ABR ladder design

Redundant live video streaming for fault tolerance

A decoding complexity may be used to predict power consumption for receiving, decoding, and/or displaying multimedia content at a wireless transmit/receive unit (WTRU). The decoding complexity may be based on decoding complexity feedback received from a reference device, such as another WTRU. The decoding complexity feedback may be based on measurements performed at the reference device for receiving decoding, and/or displaying the multimedia content. A content providing device may indicate the decoding complexity of requested media content to a WTRU, or another network entity. The decoding complexity may be indicated in a streaming protocol or file associated with the media content. The WTRU, or other network entity, may use the decoding complexity determine its preferences regarding transmission of the media content. The content providing device may determine whether to transmit the media content based on the decoding complexity and/or the preferences of the WTRU or other network entity.

Decoding complexity for mobile multimedia streaming

Techniques described herein are directed toward creating one or more 'dynamic profiles' for media (video) streaming in which an encoding bit rate (and optionally other profile settings) is optimized for particular content. More specifically, techniques involve performing one or more 'probe' encodings of the particular content to determine an encoding bit rate (and optionally other profile settings) that results in an encoding having a quality value sufficiently near (within a threshold) a target quality value.

A device may control a video communication via transcoding and/or traffic shaping. The device may include a multipoint control unit (MCU) and/or a server. The device may receive one or more video streams from one or more devices. The device may analyze a received video stream to determine a viewing parameter. The viewing parameter may include a user viewing parameter, a device viewing parameter, and/or a content viewing parameter. The device may modify a video stream based on the viewing parameter. Modifying the video stream may include re-encoding the video stream, adjusting an orientation, removing a video detail, and/or adjusting a bit rate. The device may send the modified video stream to another device. The device may determine a hit rate for the video stream based on the viewing parameter. The device may indicate the bit rate by sending a feedback message and/or by signaling a bandwidth limit.

User-adaptive video telephony

Augmented reality (AR) systems, methods, and instrumentalities are disclosed. A user's gaze point may be estimated and may be used to search for and present information, e.g., information relating to areas on which the user is focusing. The user's gaze point may be used to facilitate or enable modes of interactivity and/or user interfaces that may be controlled by the direction of view of the user. Biometric techniques may be used to estimate an emotional state of the user. This estimated emotional state may be used to be the information that is presented to the user.

Gaze-driven augmented reality

Fault-tolerant live video streaming

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.

Systems, methods, and instrumentalities are disclosed to perform rate adaptation in a wireless transmit/receive unit (WTRU). The WTRU may receive an encoded data stream, which may be encoded according to a Dynamic Adaptive HTTP Streaming (DASH) standard. The WTRU may request and/or receive the data stream from a content server. The WTRU may monitor and/or receive a cross-layer parameter, such as a physical layer parameter, a RRC layer parameter, and/or a MAC layer parameter (e.g., a CQI, a PRB allocation, a MRM, or the like). The WTRU may perform rate adaption based on the cross-layer parameter. For example, the WTRU may set the CE bit of an Explicit Congestion Notification (ECN) field based on the cross-layer parameter. The WTRU may determine to request the data stream encoded at a different rate based on the cross-layer parameter, the CE bit, and/or a prediction based on the cross-layer parameter.

Rate adaptation using network signaling

Growing community of inventors

Seattle, WA, United States of America

Yuriy Reznik