Abstract: Systems, apparatus, articles, and methods are described including operations for eye tracking based selective backlighting of a display.

Abstract: Computer-readable storage media, computing devices and methods are discussed herein. In embodiments, a computing device may include one or more display devices, a digital content module coupled with the one or more display devices, and an augmentation module coupled with the digital content module and the one or more display devices. The digital content module may be configured to cause a portion of textual content to be rendered on the one or more display devices. The textual content may be associated with a digital scene that may be utilized to augment the textual content. The augmentation module may be configured to dynamically adapt the digital scene, based at least in part on a real-time video feed, to be rendered on the one or more display devices to augment the textual content. Other embodiments may be described and/or claimed.

Abstract: Systems and methods may provide for receiving a short range signal from a sensor that is collocated with a short range display and using the short range signal to detect a user interaction. Additionally, a display response may be controlled with respect to a long range display based on the user interaction. In one example, the user interaction includes one or more of an eye gaze, a hand gesture, a face gesture, a head position or a voice command, that indicates one or more of a switch between the short range display and the long range display, a drag and drop operation, a highlight operation, a click operation or a typing operation.

Abstract: This disclosure is directed to machine learning-based user behavior characterization. An example system may comprise a device including a user interface module to present content to a user and to collect user data (e.g., including user biometric data) during the content presentation. The system may also comprise a machine learning module to determine parameters for use in presenting the content based on the user data. For example, the machine learning module may formulate a behavioral model including user states based on the user data, the user states being correlated to an objective (e.g., based on a cost function) and content presentation parameter settings. Employing the behavioral model, the machine learning module may determine a current user state based on the user data, and may select the content presentation parameter settings to bias movement of the current observed user state towards an observed user state associated with the maximized cost function.

Abstract: Methods, apparatuses and storage medium associated with engineering perceptual computing systems that includes user intent modeling are disclosed herewith. In embodiments, one or more storage medium may include instructions configured to enable a computing device to receive a usage model having a plurality of user event/behavior statistics, and to generate a plurality of traces of user events/behaviors over a period of time to form a workload. The generation may be based at least in part on the user event/behavior statistics. The workload may be for input into an emulator configured to emulate a perceptual computing system. Other embodiments may be disclosed or claimed.

Abstract: Techniques to provide efficient stereo block matching may include receiving an object from a scene. Pixels in the scene may be identified based on the object. Stereo block matching may be performed for only the identified pixels in order to generate a depth map. Other embodiments are described and claimed.

Abstract: Computer-readable storage media, computing device and methods associated with dynamic modification of a rendering of a physical scene. In embodiments, one or more computer-readable storage media may have instructions stored thereon which, when executed by a computing device, may provide the computing device with a dynamic augmentation module. The dynamic augmentation module may, in some embodiments, cause the computing device to receive a manipulation of a physical scene. In response to receipt of the manipulation, the dynamic augmentation module may cause the computing device to dynamically modify a rendering of the physical scene. In some embodiments, this may be accomplished through real-time application of one or more virtual articles to the rendering of the physical scene or alteration of one or more virtual articles added to the rendering of the physical scene. Other embodiments may be described and/or claimed.

Abstract: Computer-readable storage media, computing devices, and methods associated with an adaptive learning environment associated with an adaptive learning environment are disclosed. In embodiments, a computing device may include an instruction module and an adaptation module operatively coupled with the instruction module. The instruction module may selectively provide instructional content of one of a plurality of instructional content types to a user of the computing device via one or more output devices coupled with the computing device. The adaptation module may determine, in real-time, an engagement level associated with the user of the computing device and may cooperate with the instruction module to dynamically adapt the instructional content provided to the user based at least in part on the engagement level determined. Other embodiments may be described and/or claimed.

Abstract: Various embodiments are generally directed to techniques for providing an augmented reality view in which eye movements are employed to identify items of possible interest for which indicators are visually presented in the augmented reality view. An apparatus to present an augmented reality view includes a processor component; a presentation component for execution by the processor component to visually present images captured by a camera on a display, and to visually present an indicator identifying an item of possible interest in the captured images on the display overlying the visual presentation of the captured images; and a correlation component for execution by the processor component to track eye movement to determine a portion of the display gazed at by an eye, and to correlate the portion of the display to the item of possible interest. Other embodiments are described and claimed.

Abstract: Apparatuses, systems, media and/or methods may involve creating content. A property component may be added to a media object to impart one or more of a perceptual property or a contextual property to the media object. The property component may be added responsive to an operation by a user that is independent of a direct access by the user to computer source code. An event corresponding to the property component may be mapped with an action for the media object. The event may be mapped with the action responsive to an operation by a user that is independent of a direct access by the user to computer source code. A graphical user interface may be rendered to create the content. In addition, the media object may be modified based on the action in response to the event when content created including the media object is utilized.

Abstract: A deactivated passive user interaction sensor may be activated or deactivated on demand based on an expected use of the sensor. The expected use may be ascertained by detecting a predetermined user interaction at another sensor that is already active. Once the predetermined user interaction is detected, the active sensor may be deactivated and the sensor that is expected to be used may be activated. Total sensor power consumption may be reduced by providing a predetermined sensor activation and deactivation sequence for at least three sensors in a computing system based on predetermined user interactions with an active sensor. Methods, apparatuses, systems, and computer readable media are provided.

Abstract: Examples are disclosed for determining an interestingness score for one or more areas of interest included in a display element such as a static image or a motion video. In some examples, an interestingness score may be determined based on eye tracking or gaze information gathered while an observer views the display element.

Abstract: Systems, apparatus, articles, and methods are described including operations for eye tracking based selective backlighting of a display.

Abstract: Systems and methods may provide for receiving a short range signal from a sensor that is collocated with a short range display and using the short range signal to detect a user interaction. Additionally, a display response may be controlled with respect to a long range display based on the user interaction. in one example, the user interaction includes one or more of an eye gaze, a hand gesture, a face gesture, a head position or a voice command, that indicates one or more of a switch between the short range display and the long range display, a drag and drop operation, a highlight operation, a click operation or a typing operation.

Abstract: Technologies for depth-based gesture control include a computing device having a display and a depth sensor. The computing device is configured to recognize an input gesture performed by a user, determine a depth relative to the display of the input gesture based on data from the depth sensor, assign a depth plane to the input gesture as a function of the depth, and execute a user interface command based on the input gesture and the assigned depth plane. The user interface command may control a virtual object selected by depth plane, including a player character in a game. The computing device may recognize primary and secondary virtual touch planes and execute a secondary user interface command for input gestures on the secondary virtual touch plane, such as magnifying or selecting user interface elements or enabling additional functionality based on the input gesture. Other embodiments are described and claimed.

Abstract: Technologies for adaptively embedding an advertisement into media content via contextual analysis and perceptual computing include a computing device for detecting a location to embed advertising content within media content and retrieving user profile data corresponding to a user of a computing device. Such technologies may also include determining advertising content personalized for the user based on the retrieved user profile and embedding the advertising content personalized for the user into the media content at the detected location within the media content to generate augmented media content for subsequent display to the user.

Abstract: A device and method for timing advertisement breaks in video-on-demand applications based on viewer attention level includes a video device configured to display video content and receive biometric data indicative of the attention level of a viewer. The video device may notify a video-on-demand server that the attention level of the viewer has exceeded a threshold. In response to the notification, the video-on-demand server may determine a time to display advertisement content on the video device. The advertisement break time may be determined in relation to the video content. The advertisement content may be selected based on the video content. The video device may determine the viewer attention level during playback of the advertisement content and pause playback if the viewer attention level falls below the threshold.

Abstract: A deactivated passive user interaction sensor may be activated or deactivated on demand based on an expected use of the sensor. The expected use may be ascertained by detecting a predetermined user interaction at another sensor that is already active. Once the predetermined user interaction is detected, the active sensor may be deactivated and the sensor that is expected to be used may be activated. Total sensor power consumption may be reduced by providing a predetermined sensor activation and deactivation sequence for at least three sensors in a computing system based on predetermined user interactions with an active sensor. Methods, apparatuses, systems, and computer readable media are provided.

Abstract: Methods, apparatuses and storage medium associated with engineering perceptual computing systems that includes user intent modeling are disclosed herewith. In embodiments, one or more storage medium may include instructions configured to enable a computing device to receive a usage model having a plurality of user event/behavior statistics, and to generate a plurality of traces of user events/behaviors over a period of time to form a workload. The generation may be based at least in part on the user event/behavior statistics. The workload may be for input into an emulator configured to emulate a perceptual computing system. Other embodiments may be disclosed or claimed.

Abstract: Systems, apparatus, articles, and methods are described including operations for eye tracking based selective accentuation of portions of a display.