Amazon Technologies, Inc.

Ilya Vladimirovich Brailovskiy

Ilia Vitsnudel

Qi Keith Wang

Paul Berenberg

Naushirwan Navroze Patuck

Yongjun Wu

Manuel Rosendo Arana Manzano

Yueshi Shen

Marcus-Alan Gilbert

Evangelos Pappas-Katsiafas

Amit Kumar Agrawal

Sharadh Ramaswamy

Noam Sorek

Nathaniel Bubis

Kenneth James Albanowski

Tarek Amara

Jason Gluckman

Philip James Taylor

Dmitry Svetlov

Alessio Carosi

Raul Izahi Lopez Hernandez

Ramin Ghorashi

Stephen John Bannister

James Siminoff

Mark D Siminoff

Matthew J England

Spiro Sacre

Varadarajan Gopalakrishnan

Andrew Jay Roths

Ambrish Tyagi

Isabella Talley Lewis

Eric Gifford Marason

Raghavan Manmatha

Matthew Alan Townsend

Ilya Umansky

David Wayne Stafford

Paul Alioshin

Matthew Dale Carter

Amir Frenkel

Renganathan Veerasubramanian

Venkatesh Viswanathan

Laurent Brisedoux

Ali Shahrokni

Christopher Mark Stevens Adcock

Gordon McLean Downie

Benjamin Robert Hirsch

Ian David Skidmore

Igor Aleksandrovich Tryndin

Robert Macauley

Andrii Malivanchuk

Fernando Palomar

Manuel Rosendo Arana-Manzano

Vadym Tkachuk

Michiel Josias De Kock

Ulises Brindis

Methods of video streaming are generally described. In some examples, a camera device periodically captures an image, communicates encoded frame data representing that image to a server, and decodes and stores the previously encoded frame data as a background picture. The server receives the encoded frame data, decodes it, and stores the decoded frame in a buffer for future use. Subsequently, upon initiation of a streaming session, the camera device captures another image and encodes a predicted key frame based on differences between the captured image and the background picture. The camera device sends the predicted key frame to the server, which receives it and reconstructs a facsimile of the captured image utilizing the previously decoded frame stored in the buffer. Methods of acknowledging successfully decoded frames for use in selecting background pictures is also described.

Enhanced video streaming and reference frame synchronization

Techniques are generally described for remote estimation of bandwidth. In various examples, a video stream may be received at a first bit rate over a first communication channel. A first value of a network condition of the video stream may be determined over a first time period. A determination may be made that the first value is less than a threshold value. A first bandwidth estimate of the communication channel may be determined. The first bandwidth estimate may comprise the first bit rate reduced by a first percentage. A second value of the network condition may be determined over a second time period. A determination may be made that the second value is greater than the threshold value. A second bandwidth estimate of the communication channel may be determined. The second bandwidth estimate may be less than the first bandwidth estimate.

Bandwidth estimation for video encoding

Methods and systems for improved quality of a streaming session using multiple simultaneous streams. For the multiple simultaneous streams an audio/video device (A/V device) records and generates a high-resolution stream and a low-resolution stream for simultaneous transmission to a server. The server selects one of the two streams for retransmission to a destination client device. The server also monitors the streaming session and estimates a total available bandwidth between the server and the A/V device and assigns a confidence value to the bandwidth estimation. The server periodically transmits the bandwidth estimate and confidence value to the A/V device to improve the efficiency of the streams being generated by the A/V device. The A/V device can use the received bandwidth estimate and confidence value to adapt the resolution of each of the streams to efficiently use the total available bandwidth between the A/V device and the server.

Bandwidth estimation for video streams

This disclosure describes, in part, an audio/video (A/V) device that includes a first camera for generating first image data and one or more second cameras for both motion detection and generating second image data. For instance, the A/V device may generate and then store the second image data in one or more buffers. The A/V device may then detect an event, such as possible motion of an object. Based on detecting the event, A/V device may cause the one or more second cameras to cease generating the second image data and cause the first camera to begin generating the first image data. The A/V device may then process the second image data and send the processed second image data to a computing system. Next, the A/V device may process the first image data and send the processed first image data to the computing system.

Audio/video electronic device

Techniques are generally described for network pattern matching. In various examples, first data may be sent over a network at a first bit rate to a second device. A plurality of network congestion profiles of the network may be stored in a memory. Network conditions of the network may be determined over a first period of time. A correlation between the network conditions and a first network congestion profile of the plurality of network congestion profiles may be determined. A second bit rate may be determined based on the first network congestion profile. Second data may be sent over the network to the second device at the second bit rate.

Network pattern matching

This disclosure describes, in part, techniques for selecting encoding parameters for an electronic device. For instance, remote system(s) may receive, from the electronic device, video data representing a video. The remote system(s) may then analyze the video data to identify portions of the video that represented different areas located within the field of view (FOV) of the electronic device. The areas may include static areas, which do not include recurring motion, and/or dynamic areas, which include recurring motion. Additionally, the remote system(s) may analyze the video data to select encoding parameters for encoding the video data and/or for encoding the portions of the video data that represent the identified areas. The electronic device may then receive the encoding parameters from the remote system(s) and use the encoding parameters to encode additional video data that is generated by the electronic device.

Techniques for encoding video data

An embodiment of a camera device may include an optical filter. The camera device may attempt to actuate the optical filter from an inactive position to an active position, record video, count a quantity of pixels, and/or a quantity of lines of pixels, in one or more frames of the video that are a color that is characteristic of the absence of the optical filter, determine that the quantity is greater than a threshold, and again attempt to move the optical filter to its active position.

Detection and correction of optical filter position in a camera device

Techniques are generally described for compression encoding of images. In various examples, the techniques may comprise receiving image data. In some examples, the techniques may further comprise generating a first compressed representation of luminance values of the image data by encoding luminance values of the image data with reference to a luminance palette. In some examples, the techniques may further include generating a second compressed representation of chrominance values of the image data by applying a frequency domain based image transform to the chrominance values of the image data. In various further examples, the techniques may further comprise combining the first compressed representation and the second compressed representation to generate compressed image data.

Compression encoding of images

Methods to switch between renditions of a video stream are generally described. In some examples, the methods may include encoding a video stream at a first image quality in a first rendition and a second, lower image quality in a second rendition. The methods may further include sending the first rendition to a recipient computing device. The methods may include receiving a request to switch from the first rendition to the second rendition. The methods may include determining that first indicator data of a first inter-coded frame indicates that the video stream can be switched to a lower image quality rendition at the first inter-coded frame. In some examples, the methods may further include sending the second rendition to the recipient computing device.

Rendition switch indicator

Methods of video streaming are generally described. In some examples, the methods may be performed by a server device and may include generating first intra-coded frame (I-frame) data and a plurality of enhancement layer data corresponding to the first I-frame data. The methods may further include sending the first I-frame data to a client device. The methods may further include transmitting first enhancement layer data to the client device. The methods may include sending first inter-coded frame data to the client device. In some examples, the first inter-coded frame data can be decoded by referencing first reference frame data generated by combining the first I-frame data and the first enhancement layer data.

Enhanced encoding and decoding of video reference frames

Techniques are generally described for catch-up pacing for video streaming. In various examples, a camera may capture first video data representing a physical environment. In some examples, motion in the physical environment may be detected from the first video data. A communication channel may be established with a remote computing device. In some examples, the camera may capture second video data. In various examples, the second video data may be captured during a period of time corresponding to the establishment of the communication channel. An available bandwidth of the communication channel may be determined. The available bandwidth may comprise a first bitrate. Third video data may be captured by the camera. The third video data may be encoded at a second bitrate lower than the first bitrate. The first video data, second video data and third video data may be sent to the remote computing device.

Catch-up pacing for video streaming

Techniques are generally described for compression encoding and decoding of video frames. In various examples, the techniques may include generating first reference frame data, first enhancement layer data corresponding to the first reference frame data, and second enhancement layer data corresponding to the first reference frame data. In various examples, the techniques may further include sending the first reference frame data, the first enhancement layer data, and the second enhancement layer data to at least one recipient computing device. The techniques may further include determining that the recipient computing device did not receive first unreceived data. In some examples, the first unreceived data may comprise at least one of the first reference frame data, the first enhancement layer data, and the second enhancement layer data. In other examples, the techniques may include resending the first unreceived data to the recipient computing device.

Techniques are generally described for enhanced compression of video data. In various examples, the techniques may include receiving first video data representing a scene in an environment. The techniques may further include generating illumination map data representing illumination of the scene in the first video data. The techniques may further comprise generating reflectance map data representing a reflectance of at least one object in the first video data. In some examples, the techniques may include sending, to a second computing device, the illumination map data and the reflectance map data. The techniques may further include receiving second video data representing the scene. The techniques may include determining a first illumination difference between the second video data and the first video data. The techniques may comprise sending, to the second computing device, the first illumination difference.

Enhanced compression of video data

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Mountain View, CA, United States of America

Ilya Vladimirovich Brailovskiy