Samsung Electronics Co., Ltd.

Google Inc.

Ayesha Mudassir Khwaja

Sajid Hassan Sadi

Rahul Budhiraja

Pranav K Mistry

Sergio Perdices-Gonzalez

Brian Dongwoo Lee

Jawahar Jain

Cody Blair Wortham

James Young

Wei Wang

Brian Thomas Harms

Cathy Kim

Ranhee Chung

Link Chun Huang

Iliya Tsekov

Rebecca Gisoo Park Chiou

Ruokan He

Joseph Joseph Cherukara

Yedan Qian

Junyeon Cho

Jason Yeh

Usman Abdullah

Sangwoo Han

Michael Noh

Aditi Bhargava

Mariia Sandrikova

Abhijith Shastry

Haiyue Yu

Paul Dunlop

Shashank Goyal

Subash Gutala

Xiansha Jin

Richard Ledley

Yale Thomas

Curtis Robinson

Brandon Maxwell

Andres Calvo

Gustav Sennton

Milo Sredkov

Hanfu Zhang

Soichan Nget

Dru Nget

Brian Harms

Implementations described herein relate to methods, systems, and computer-readable media to automatically answer a call. In some implementations, a method includes receiving a call from a caller device at a client device. The method further includes determining, based on an identifier associated with the call, whether the call matches auto answer criteria, and yin response to determining that the call matches the auto answer criteria, answering the call without user input and without alerting a user of the client device. The method further includes generating a call embedding for the call based on received audio of the call, comparing the call embedding with spam embeddings to determine whether the call is a spam call, and in response to determining that the call is a spam call, terminating the call.

Automatic call categorization and screening

In one embodiment, a method includes presenting to a user, on a display of a head-worn client computing device, a three-dimensional video including images of a real-life scene that is remote from the user's physical environment. The method also includes presenting to the user, on the display of the head-worn client computing device, a graphical object including an image of the user's physical environment or a virtual graphical object.

Presentation of three-dimensional video

In one embodiment, a method includes accessing a first image and a second image, where at least part of the first image overlaps with at least part of the second image. The first and second images are divided into portions associated with a first set of grid points, where each grid point in the first set corresponds to a portion of the first image or the second image. Differences in the region of overlap between the first and second images are determined. One or more grid points in the first set and the corresponding portions of the first image or the second image are moved relative to one or more other grid points in the first set based on the determined differences.

Seamless image stitching

In one embodiment, a computer-readable non-transitory storage medium embodies software that is operable when executed to, in real time, capture a number of images of a user; identify one or more regions of interest corresponding to one or more superficial arteries of the user. The identification is based on a signal-to-noise ratio of photoplethysmogram (PPG) data obtained from the plurality of images. The software is further operable to measure, based on the PPG data, blood volume pulse (BVP) signals; and based on the measured BVP signals, compute one or more cardiological metrics for the user.

Determining artery location using camera-based sensing

In one embodiment, a computer-readable non-transitory storage medium embodies software that is operable when executed to, in real time, capture a number of images of a user; and determine a time-series signal for the user based on the plurality of images. The signal includes one or more segments that are physiologically plausible and one or more segments that are physiologically implausible. The software is further operable to identify one or more of the physiologically plausible sub-segments based on one or more pre-defined signal characteristics; and calculate one or more heartrate measurements based on the physiologically plausible sub-segments.

Determining cardiovascular features using camera-based sensing

In one embodiment, a computer-readable non-transitory storage medium embodies software that is operable when executed to, in real time, capture, by a single sensor, a number of images of a user; determine, based on the number of images, one or more short-term cardiological signals of the user during a period of time; estimate, based on the cardiological signals, a first short-term emotional state of the user; determine, based on the number of images, one or more short-term neurological signals of the user during the period of time; estimate, based on the neurological signals, a second short-term emotional state of the user; compare the first estimated emotional state to the second estimated emotional state; and in response to a determination that the first estimated emotional state corresponds to the second estimated emotional state, determine a short-term emotion of the user during the period of time.

Determining emotions using camera-based sensing

In one embodiment, an apparatus includes a processor and multiple pairs of cameras, where each camera of a first pair of cameras is separated from each other by one camera of a second pair of cameras. Each camera of the first pair of cameras has a first orientation, and each camera of the second pair of cameras has a second orientation that is different from the first orientation.

Camera system for three-dimensional video

In one embodiment, a method includes receiving, from a client device, a request corresponding to a particular view of a three-dimensional video comprising multiple views. The method also includes accessing a data stream corresponding to the video. The method further includes selecting, based on the request, one or more portions of the accessed data stream, at least one of the selected portions corresponding to the particular view. The method also includes transmitting the selected portion of the accessed data stream to the client device.

Transmission of three-dimensional video

In one embodiment, a method includes receiving multiple images from multiple cameras, where the multiple cameras include a first camera having a first orientation and a second camera having a second orientation, and the multiple images include a first image from the first camera and a second image from the second camera. The method also includes detecting multiple feature points within the first and second images. The method further includes determining one or more pairs of corresponding feature points located within a region of overlap between the first and second images, where the pairs of corresponding feature points include a respective one of the feature points from each of the first and second images. The method also includes spatially adjusting the first or second image based on a calculated offset between each pair of corresponding feature points.

Image stitching for three-dimensional video

In one embodiment, a method includes accessing multiple images representing a 360&#xb0; view of a scene, each image representing a portion of the 360&#xb0; scene and including a first overlap area and a second overlap area, the first overlap area corresponding to an overlap with a first adjacent image, and the second overlap area corresponding to an overlap with a second adjacent image. The method also includes, calculating, for each overlap area, a set of homographies based on one or more feature points in the overlap area. The method further includes creating a set of left images from the multiple images, the set of left images representing a first 360&#xb0; view of the scene. The method also includes creating a set of right images from the multiple images, the set of right images representing a second 360&#xb0; view of the scene.

Reconstruction of three-dimensional video

Growing community of inventors

Stanford, CA, United States of America

Ayesha Mudassir Khwaja