Lenovo (singapore) Pte. Ltd.

Motorola Mobility LLC

Krishna C Garikipati

John Weldon Nicholson

David Alexander Schwarz

Jun-Ki Min

Song Wang

Ming Qian

Mir Farooq Ali

Jun Ki Min

In one aspect, a device includes at least one processor and storage accessible to the at least one processor. The storage comprises instructions executable by the at least one processor to determine an attention center that corresponds to at least a portion of a real-world environment and present, on a display, content at a display location determined based on the attention center.

Presentation of content based on attention center of user

An approach is provided that captures a set of sequential images of an area where there is a selected moving object. Both a keypoint-based (KP-based) matching model and a neural network based (NN-based) matching model are used with the KP-based matching model analyzing most or all of the captured images and the NN-based model being more computational intensive and analyzing a subset of the images. When the KP-based matching model fails to identify the selected object in an image, the NN-based model is used to find the object so that the KP-based matching model can re-establish tracking of the object.

Recover keypoint-based target tracking from occlusion using deep neural network segmentation

A method, a system, and a computer program product for indicating a dialogue status of a conversation thread between a user of an electronic device and a virtual assistant capable of maintaining conversational context of multiple threads at a time. The method includes receiving, at an electronic device providing functionality of a virtual assistant (VA), a user input that corresponds to a task to be performed by the VA. The method includes determining, from among a plurality of selectable threads being concurrently maintained by the VA and based on content of the user input, one target thread to which the user input is associated. The method includes performing the task within the target thread.

Methods to present the context of virtual assistant conversation

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Chicago, IL, United States of America

Krishna C Garikipati