Abstract: Techniques are disclosed herein to perform user/device interaction tasks for electronic devices (e.g., wearable devices) with greater efficiency—and while leveraging information streams gathered by multiple types of input modalities (e.g., captured video images, as well as inertial measurement unit (IMU) data, or the like). Performance of such user/device interaction tasks are desirably able to leverage a user's natural head pointing direction, thereby enabling touchless input. According to some embodiments, the user's “relative” head motion (which has been determined to be more robust than a user's eye gaze or “absolute” head pointing direction—especially when the user is in low lighting conditions, being captured by a low-resolution camera, and/or when the area around the user's eyes is occluded), e.g., as determined from images captured by one or more integrated device cameras, may be used to determine the selection of particular UI elements on a display screen of the electronic device.

Abstract: This disclosure relates generally to the field of user/device interactions. More particularly, it relates to techniques for detecting when a user's attention is directed at an electronic device, e.g., as determined based, at least in part, on analysis of images captured by one or more cameras integrated in the electronic device. Attention awareness can help to reduce the power and/or computing resources consumed by the electronic device, e.g., by only providing certain user experiences at the electronic device when they are actually likely to be desired by the user. In some embodiments, an attention awareness algorithm may be initiated by some triggering event or action. Once initiated, images captured by a camera of the electronic device may be fed to an attention detection algorithm to determine whether the user's head is in a pose where the algorithm believes that the user likely desires to interact with the device's user interface.

Abstract: A collaborative work environment supports manipulating an object defined by a three-dimensional model by multiple remote participants. A three-dimensional model of the object is able to be translated, rotated and scaled in a work area of a whiteboard associated with the collaborative work environment. Each of the remote participants is able to view, manipulate, and mark-up the three-dimensional model of the object so that the remote participants can work collaboratively together.

Abstract: A system and method for increasing the performance associated with creating simulated 3D worlds from a network. The system and method provides a means for increasing the performance by fetching objects in the order of their importance. A priority scheme is used to determine the fetching, pre-fetching, and caching of URLs. The operations of assigning priorities, making prefetch requests and cache management is driven by data in an asset database table. The database contains information pertaining to each asset within the current scene such as the priority, status, region, type bounds, and retrieval time. The asset database table is updated based on fetching activities, camera position, and the positions of moving assets. A world scene is subdivided into appropriately sized regions when a scene is first downloaded. Asset type origins are defined and moved, based on the position, orientation, and velocity of the camera. Regions are assigned priorities based on their distance from the asset origin.

Abstract: A collaborative work environment supports manipulating an object defined by a three-dimensional model by multiple remote participants. A three-dimensional model of the object is able to be translated, rotated and scaled in a work area of a whiteboard associated with the collaborative work environment. Each of the remote participants is able to view, manipulate, and mark-up the three-dimensional model of the object so that the remote participants can work collaboratively together.

Abstract: A method for selecting a three-dimensional object in a three-dimensional environment improves a speed and efficiency of a lassoing technique. The method reduces the number of objects that have to be rendered into images in order to determine whether the object is included within an area selected by the lasso. The method selects objects intersected by the lasso using ray picking. These selected objects are not rendered into images. The method determines those objects whose bounding boxes do not intersect a bounding box of the area selected by the lasso. These objects are also not rendered into images. The method renders the remaining objects into images to determine which are included with the area selected by the lasso.