Qualcomm Incorporated

Intel Corporation

Vinesh Sukumar

Miran Chun

Daniel Jared Sinder

Wesley James Holland

Jian Shen

Ziad Asghar

Vikram Gupta

Khaled Helmi El-maleh

Tae-Hoon Kim

Joel Linsky

Michael Franco Taveira

Seyfullah Halit Oguz

Fatih Murat Porikli

Geoffrey Francis Burns

Paul Torres

Systems and techniques are provided for conditioning virtual representatives. For example, a method can include obtaining, by a conditioning engine, a baseline model for a virtual representative; obtaining, by the conditioning engine, one or more conditioning inputs configured to condition an action in one or more multi-user experiences of the virtual representative; generating, based on the baseline model and the one or more conditioning inputs configured to condition an action in one or more multi-user experiences of the virtual representative, a conditioned model for the virtual representative; and outputting the conditioned model for the virtual representative.

Virtual representative conditioning system

Systems and techniques are provided for coordinating multi-user experiences. For example, a process can include obtaining a plurality of settings associated with a plurality of multi-user experience participants. The plurality of settings includes one or more arbitrated settings and one or more non-arbitrated settings. The process can include arbitrating, by a settings arbitration engine, the one or more arbitrated settings to generate one or more adjusted settings for each arbitrated setting. The process can include generating, by an experience adaptation engine, an adapted multi-user experience, wherein the adapted multi-user experience is configured to enforce the one or more adjusted settings for each arbitrated setting.

Multi-user experience coordination system

Systems and techniques are provided for processing audio data. For instance, a process can include detecting a first audio data between two or more in-person participants of a plurality of in-person participants of a group communication session. The first audio data can be identified as private based on one or more cues associated with the first audio data. A second audio data can be identified between the two or more in-person participants. The second audio data can be identified as non-private based on one or more additional cues associated with the second audio data, wherein the one or more additional cues associated with the second audio data are different from the one or more cues associated with the first audio data. The second audio data can be output based on identifying the second audio data as non-private.

Systems and methods for improved group communication sessions

Techniques are provided for motion estimation using hybrid video imaging based on frame-based capture and event-based capture. A methodology implementing the techniques according to an embodiment includes receiving a sequence of pixel events, generated asynchronously by an event-based video camera, and receiving a sequence of image frames generated by a frame-based video camera at a frame sampling period. The method also includes integrating a subset of the sequence of pixel events, occurring within the frame sampling period between two of the image frames, to generate a pixel motion vector representing motion of the pixel between the two image frames. The method further includes mapping the pixel motion vector to a tile of one of the image frames to generate an estimated motion vector associated with that tile.

Motion estimation using hybrid video imaging system

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Fremont, CA, United States of America

Vinesh Sukumar