Abstract:
Techniques for auto-generating the target's visual representation may reduce or eliminate the manual input required for the generation of the target's visual representation. For example, a system having a capture device may detect various features of a user in the physical space and make feature selections from a library of visual representation feature options based on the detected features. The system can automatically apply the selections to the visual representation of the user based on the detected features. Alternately, the system may make selections that narrow the number of options for features from which the user chooses. The system may apply the selections to the user in real time as well as make updates to the features selected and applied to the target's visual representation in real time.
Abstract:
Data captured with respect to a human may be analyzed and applied to a visual representation of a user such that the visual representation begins to reflect the behavioral characteristics of the user. For example, a system may have a capture device that captures data about the user in the physical space. The system may identify the user's characteristics, tendencies, voice patterns, behaviors, gestures, etc. Over time, the system may learn a user's tendencies and intelligently apply animations to the user's avatar such that the avatar behaves and responds in accordance with the identified behaviors of the user. The animations applied to the avatar may be animations selected from a library of pre-packaged animations, or the animations may be entered and recorded by the user into the avatar's avatar library.
Abstract:
A capture device may capture a user's motion and a display device may display a model that maps to the user's motion, including gestures that are applicable for control. A user may be unfamiliar with a system that maps the user's motions or not know what gestures are applicable for an executing application. A user may not understand or know how to perform gestures that are applicable for the executing application. User motion data and/or outputs of filters corresponding to gestures may be analyzed to determine those cases where assistance to the user on performing the gesture is appropriate.
Abstract:
A system and method are disclosed for delivering content customized to the specific user or users interacting with the system. The system includes one or more modules for recognizing an identity of a user. These modules may include for example a gesture recognition engine, a facial recognition engine, a body language recognition engine and a voice recognition engine. The user may also be carrying a mobile device such as a smart phone which identifies the user. One or more of these modules may cooperate to identify a user, and then customize the user's content based on the user's identity. In particular, the system receives user preferences indicating the content a user wishes to receive and the conditions under which it is to be received. Based on the user preferences and recognition of a user identity and/or other traits, the system presents content customized for a particular user.
Abstract:
A system and method are disclosed for recognizing and tracking a user's skeletal joints with a NUI system and further, for recognizing and tracking only some skeletal joints, such as for example a user's upper body. The system may include a limb identification engine which may use various methods to evaluate, identify and track positions of body parts of one or more users in a scene. In examples, further processing efficiency may be achieved by segmenting the field of view in smaller zones, and focusing on one zone at a time. Moreover, each zone may have its own set of predefined gestures which are recognized.
Abstract:
Systems, methods and computer readable media are disclosed for gesture shortcuts. A user's movement or body position is captured by a capture device of a system, and is used as input to control the system. For a system-recognized gesture, there may be a full version of the gesture and a shortcut of the gesture. Where the system recognizes that either the full version of the gesture or the shortcut of the gesture has been performed, it sends an indication that the system-recognized gesture was observed to a corresponding application. Where the shortcut comprises a subset of the full version of the gesture, and both the shortcut and the full version of the gesture are recognized as the user performs the full version of the gesture, the system recognizes that only a single performance of the gesture has occurred, and indicates to the application as such.
Abstract:
A system and method are disclosed for combining interactive gaming aspects into a linear story. A user may interact with the linear story via a NUI system to alter the story and the images that are presented to the user. In an example, a user may alter the story by performing a predefined exploration gesture. This gesture brings the user into the 3-D world of the displayed image. In particular, the image displayed on the screen changes to create the impression that a user is stepping into the 3-D virtual world to allow a user to examine virtual objects from different perspectives or to peer around virtual objects.
Abstract:
Data captured with respect to a human may be analyzed and applied to a visual representation of a user such that the visual representation begins to reflect the behavioral characteristics of the user. For example, a system may have a capture device that captures data about the user in the physical space. The system may identify the user's characteristics, tendencies, voice patterns, behaviors, gestures, etc. Over time, the system may learn a user's tendencies and intelligently apply animations to the user's avatar such that the avatar behaves and responds in accordance with the identified behaviors of the user. The animations applied to the avatar may be animations selected from a library of pre-packaged animations, or the animations may be entered and recorded by the user into the avatar's avatar library.
Abstract:
A system and method is disclosed for sensing, storing and using personal trait profile data. Once sensed and stored, this personal trait profile data may be used for a variety of purposes. In one example, a user's personal trait profile data may be accessed and downloaded to different computing systems with which a user may interact so that the different systems may be instantly tuned to the user's personal traits and manner of interaction. In a further example, a user's personal trait profile data may also be used for authentication purposes.