Microsoft Technology Licensing, LLC

James Kai Yu Lau

Raman Kumar Sarin

Jae Pum Park

Monica Estela Gonzalez Veron

Joseph H Matthews, Iii

Miller Thomas Abel

Motaz Ahmad El-Saban

Ayman Kaheel

Mohamed Shawky

Kenneth Paul Hinckley

Moe Khosravy

Jyh-Han Lin

Shai Herzog

John Peter Bruno, Jr

Karon Weber

Sumit Kumar

Monica Gonzalez

Ahmed El Baz

Tamer Deif

Alaa Abdel-Hakim Aly

Shai Guday

James M Lyon

Richard Yuqi Yao

Katrika Marie Morris

Katrika Marie Woodcock

Joseph Futty

Apparatus and methods are disclosed for selecting one or more mobile device applications using context data describing the current environment of a mobile device and application metadata describing environment conditions where applications are more likely to be relevant, in order to improve the experience of discovering, downloading, and installing mobile device applications. According to one embodiment, a method comprises associating metadata with mobile device applications automatically receiving context data representing a current geographical location from a mobile phone, searching the metadata to determine which applications are likely of interest based on the current geographical location, and transmitting notification data to the mobile phone indicating the determined applications.

Location and contextual-based mobile application promotion and delivery

Viral application distribution facilitates distribution of an application among users and increases likelihood of downloading the application by the users. A first device may receive information of an application from a second device through a short-range communication channel. The information may comprise identification information of the application without any personally identifiable information of the second device to protect privacy of a user of the second device. A version of the application that is compatible with the first device is determined by searching a catalog using the identification information of the application. The compatible version of the application may then be downloaded or obtained by the first device. Location-based viral distribution may also be performed between devices that visit a location, even at different times.

Viral application distribution

Exemplary methods, apparatus, and systems are disclosed for authenticating a user to computing device. In one exemplary embodiment, an indication of a request by a user to unlock a mobile device in a locked state is received. One or more images of the face of the user are captured. Facial components of the user from the one or more captured images are extracted. A determination is made as to whether the user is an authorized user or a non-authorized user based at least in part on a comparison of the facial components of the user extracted from the one or more captured images to facial components of the authorized user from one or more authentication images of the authorized stored on the mobile device. If the user is determined to be the authorized user, the mobile device unlocked; otherwise, the mobile device is maintained in its locked state.

Using facial data for device authentication or subject identification

Determining geospatial patterns from device data collected from a plurality of computing devices. The devices represent, for example, a plurality of sources providing the device data. The device data describes the computing devices and/or environments thereof. Some embodiments present the determined patterns to users for editing, update maps with the edited patterns, and distribute the maps to the users. The maps are stored to create a searchable map library.

Identifying geospatial patterns from device data

The present disclosure relates to a mobile phone and a method for answering such a phone automatically without user input. In one embodiment, the mobile phone detects that a call is being received. A proximity sensor is then used to detect the presence of a nearby object. For example, this allows a determination to be made whether the mobile phone is within a pocket of the user while the phone is ringing. Then a determination is made whether the proximity sensor changes states. For example, if a user removes the phone from their pocket, the proximity sensor switches from detecting something proximal to detecting that the phone is no longer in the user's pocket. Next, a determination is made whether the proximity sensor is again next to an object, such as an ear. If so, the mobile phone can be automatically answered without further user input.

Automatic answering of a mobile phone

Apparatus and methods are disclosed for modifying video based on user input and or face detection data received with a mobile device to generate foreground regions (e.g., to separate a user image from background in the video). According to one disclosed embodiment, a method comprises receiving user input and/or face regions generated with a mobile device, producing an initial representation for segmenting input video into a plurality of portions based on the user input, where the initial representation includes probabilities for one or more regions of the input video being designated as foreground regions or background regions. Based on the initial representation, input video is segmented by designating one or more of the regions of the input video as foreground regions or background regions.

Modifying video regions using mobile device input

A computing device (e.g., a smart phone, a tablet computer, digital camera, or other device with image capture functionality) causes an image capture device to capture one or more digital images based on audio input (e.g., a voice command) received by the computing device. For example, a user's voice (e.g., a word or phrase) is converted to audio input data by the computing device, which then compares (e.g., using an audio matching algorithm) the audio input data to an expected voice command associated with an image capture application. In another aspect, a computing device activates an image capture application and captures one or more digital images based on a received voice command. In another aspect, a computing device transitions from a low-power state to an active state, activates an image capture application, and causes a camera device to capture digital images based on a received voice command.

Voice-controlled camera operations

Techniques and tools are described for controlling an audio signal of a mobile device. For example, information indicative of acceleration of the mobile device can be received and correlation between the information indicative of acceleration and exemplar whack event data can be determined. An audio signal of the mobile device can be controlled based on the correlation.

Controlling audio of a device

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Bellevue, WA, United States of America

James Kai Yu Lau