Apple Inc.

Nex Team Inc.

Jorge S Fino

Bradford Allen Moore

Imran A Chaudhri

Anton M Davydov

Policarpo Bonilla Wood

Emanuele Vulcano

Stephen Olivier Lemay

Scott M Herz

Jonathan P Ive

Marcel Van Os

Joshua C Weinberg

Mark B Larus

Sarah G Barbour

Duncan Robert Kerr

Bartley K Andre

Richard P Howarth

Eugene Antony Whang

Peter N Russell-Clarke

Christopher J Stringer

Martha Evans Hankey

Rico L Zorkendorfer

Daniele De Iuliis

Jody R Akana

Daniel J Coster

Matthew Dean Rohrbach

Jeremy D Bataillou

Shin Nishibori

Henrique Dias Penha

Donald Walter Pitschel

Benjamin A Rottler

Justin Edward Santamaria

Jeremiah Daniel Shaw

Lia T Napolitano

Grace H Hwang

Bob Bradley

Emily Clark Schubert

Joshua H Shaffer

Keng Fai Lee

Qi Zhang

Jason A Skinder

Eric S Lee

Sharon E Friesen

Aurelio Guzmán

Chanaka G Karunamuni

Richard R Dellinger

Jesse William Boettcher

Bryan J James

Dmitri Cavander

Prashanth Ramachandran

Allen Paul Haughay, Jr

On Loy Sung

Mini Ham

Man Hon Chan

Justin Garcia

Policarpo Bonilla Wood, Jr

Imran Chaudhri, Iii

Christine B McGavran

Jeffrey Theodore Lee

Eugene Dvortsov

Wesley Yue

Long Mak

Ashley Barton Clark

Daniel Dejos

Eric Lee

Display screen or portion thereof with graphical user interface

Systems and processes are disclosed for operating a digital assistant in a media environment. In an exemplary embodiment, a user can interact with a digital assistant of a media device while content is displayed by the media device. In one approach, a plurality of exemplary natural language requests can be displayed in response to detecting a user input of a first input type. The plurality of exemplary natural language requests can be contextually-related to the displayed content. In another approach, a user request can be received in response to detecting a user input of a second input type. A task that at least partially satisfies the user request can be performed. The performed task can depend on the nature of the user request and the content being displayed by the media device. In particular, the user request can be satisfied while reducing disruption to user consumption of media content.

Intelligent automated assistant in a media environment

A computer-implemented method for video processing is disclosed. The method includes receiving an input video of one or more persons from a camera; detecting a sequence of human poses in the input video using an artificial intelligence (AI) based technique; selecting a proper pose from among multiple poses in a given frame of the input video, to generate a sequence of proper poses; detecting one or more key points in the sequence of proper poses; computing changes in coordinates of the one or more key points; computing a function of the changes in the coordinates of the one or more key points in the sequence of proper poses; counting a given user movement as a repetitive motion of an activity based on the function; and computing a plurality of statistics about the activity based on the counting. In some embodiments, the activity is running, jogging, walking jumping, performing jumping jacks, squatting, and/or dribbling.

Video-based motion counting and analysis systems and methods for virtual fitness application

Some embodiments provide a method for an application executing on a mobile device. The method renders an animated navigation presentation for output to an external display screen not part of the mobile device. The navigation presentation includes an animated map showing at least a portion of a route to a destination. The method simultaneously displays information regarding a maneuver along the route on a display screen of the mobile device without displaying a same animated map on the mobile device. In some embodiments, the displayed information regarding the maneuver comprises a graphical instruction and a text instruction for a next maneuver along the route.

Mapping application with turn-by-turn navigation mode for output to vehicle display

Methods and systems are disclosed for pose comparison, interactive physical gaming, and remote fitness training on a user computing device. The methods and systems are configured to first receive a reference feature generated from a frame of a reference video, the reference feature computed from a reference posture of a reference person in the frame of the reference video. Next, receive a frame of a user video, the frame of the user video comprising a user. Next, extract a user posture from the frame of the user video, by performing a machine learning-based computer vision algorithm that detects one or more body key points of the user in an image plane of the user video. Finally, generate a user feature from the user posture; and determine an output score based on a distance between the reference feature and the user feature.

Pose comparison systems and methods using mobile computing devices

In some implementations, a user can play a music track from a dynamically generated playlist. The user can provide input indicating that the user likes or dislikes the music track and the playlist can be adjusted based on the user input. In some implementations, information can be presented to the user so that the user can preview changes to the playlist before the changes are made to the playlist. In some implementations, a user can adjust playlist criteria (configuration) by adjusting specific music characteristics. In some implementations, a user can adjust playlist criteria by manipulating a list of representative music tracks. In some implementations, a user can compare the user's playlist to playlists of other users.

Playlist configuration and preview

In some implementations, a mobile device transmit traffic information to a server for analysis. The traffic information includes movement information including detected stops and durations of detected stops. The traffic information is analyzed to detect traffic patterns that indicate locations of stop signs and/or stop lights. The traffic information is analyzed to determine durations of stops at stop signs and/or stop lights. The durations of stops is associated with a time of day and/or day of the week. In some implementations, navigational routes is determined based stop sign and/or stop light information, including the delays attributable to detected stop signs and/or stop lights.

Routing based on detected stops

Some embodiments provide a mapping application that provides a variety of UI elements for allowing a user to specify a location (e.g., for viewing or serving as route destinations). In some embodiments, these location-input UI elements appear in succession on a sequence of pages, according to a hierarchy that has the UI elements that require less user interaction appear on earlier pages in the sequence than the UI elements that require more user interaction. In some embodiments, the location-input UI elements that successively appear in the mapping application include (1) selectable predicted-destination notifications, (2) a list of selectable predicted destinations, (3) a selectable voice-based search affordance, and (4) a keyboard. In some of these embodiments, these UI elements appear successively on the following sequence of pages: (1) a default page for presenting the predicted-destination notifications, (2) a destination page for presenting the list of predicted destinations, (3) a search page for receiving voice-based search requests, and (4) a keyboard page for receiving character input.

Map application with improved search tools

A system and method for implementing a virtual fitness application are disclosed. Embodiments may be built for various platforms, including web browsers and mobile phones. One embodiment uses pose estimation to count the repetitive motions of a fitness activity (e.g., running). In one embodiment, to count the repetitive motions, a repetitive motion counting process is used that is based on computing differences of Y-coordinates of key points of the user. The repetitive motion counting process includes selecting a proper pose of the user; computing one or more delta values (corresponding to Y-coordinate changes of the key points); and counting a given user movement as a repetitive motion based on a function (e.g., average) of the delta values. One embodiment uses the pose estimation and repetitive motion count results to provide a gamified experience, for example, a leaderboard, a stats report, instant visual feedback, badges, coins, and a social experience.

At a portable electronic device that includes a portable-device display and is in communication with a vehicle display, displaying a first user interface on the portable-device display. Sending, from the portable electronic device to the vehicle display, information for generating a second user interface, the second user interface including an affordance. While the second user interface is displayed on the vehicle display, detecting an input activating the affordance in the second user interface, and in response, causing the portable electronic device to invoke a digital assistant. In response to invoking the digital assistant, prompting a user for an audible request. In response to receiving the audible request, causing display, within the second user interface, of a digital assistant dialogue box; and subsequently causing display, within the second user interface, of a user interface object associated with a search result, and maintaining the first user interface on the portable-device display.

Device, method, and graphical user interface for synchronizing two or more displays

In some implementations, a mobile device transmits traffic information to a server for analysis. The traffic information includes movement information including detected stops and durations of detected stops. The traffic information is analyzed to detect traffic patterns that indicate locations of stop signs and/or stop lights. The traffic information is analyzed to determine durations of stops at stop signs and/or stop lights. The durations of stops is associated with a time of day and/or day of the week. In some implementations, navigational routes is determined based stop sign and/or stop light information, including the delays attributable to detected stop signs and/or stop lights.

Growing community of inventors

Cupertino, CA, United States of America

Jorge S Fino