Abstract: A virtual skeleton includes a plurality of joints and provides a machine readable representation of a human target observed with a three-dimensional depth camera. A relative position of a hand joint of the virtual skeleton is translated as a gestured aiming vector control, and a virtual weapon is aimed in proportion to the gestured aiming vector control.

Abstract: Various embodiments are disclosed that relate to negatively matching users over a network. For example, one disclosed embodiment provides a method including storing a plurality of user profiles corresponding to a plurality of users, each user profile in the plurality of user profiles including one or more user attributes, and receiving a request from a user for a list of one or more suggested negatively matched other users. In response to the request, the method further includes ranking each of a plurality of other users based on a magnitude of a difference between one or more user attributes of the user and corresponding one or more user attributes of the other user, and sending a list of one or more negatively matched users to the exclusion of more positively matched users based on the ranking.

Abstract: A method of finding a new social network service friend for a player belonging to a social network service and having a friend group including one or more player-accepted friends includes recognizing the player, automatically identifying an observer within a threshold proximity to the player, and adding the observer to the friend group of the player in the social network service if the observer satisfies a friending criteria of the player.

Abstract: A method of matching a player of a multi-player game with a remote participant includes recognizing the player, automatically identifying an observer within a threshold proximity to the player, using an identity of the observer to find one or more candidates to play as the remote participant of the multi-player game, and when selecting the remote participant, choosing a candidate from the one or more candidates above a non-candidate if the candidate satisfies a matching criteria.

Abstract: Depth-image analysis is performed with a device that analyzes a human target within an observed scene by capturing depth-images that include depth information from the observed scene. The human target is modeled with a virtual skeleton including a plurality of joints. The virtual skeleton is used as an input for controlling a driving simulation.

Abstract: A virtual skeleton includes a plurality of joints and provides a machine readable representation of a human target observed with a three dimensional depth camera. A relative position of a hand joint of the virtual skeleton is translated as a gestured aiming vector control, and a virtual weapon is aimed in proportion to the gestured aiming vector control.

Abstract: Implementations for identifying, capturing, and presenting high-quality photo-representations of acts occurring during play of a game that employs motion tracking input technology are disclosed. As one example, a method is disclosed that includes capturing via an optical interface, a plurality of photographs of a player in a capture volume during play of the electronic game. The method further includes for each captured photograph of the plurality of captured photographs, comparing an event-based scoring parameter to an event depicted by or corresponding to the captured photograph. The method further includes assigning respective scores to the plurality of captured photographs based, at least in part, on the comparison to the even-based scoring parameter. The method further includes associating the captured photographs at an electronic storage media with the respective scores assigned to the captured photographs.

Abstract: A virtual skeleton includes a plurality of joints and provides a machine readable representation of a human target observed with a three-dimensional depth camera. A relative position of a hand joint of the virtual skeleton is translated as a gestured control, and a three-dimensional virtual world is controlled responsive to the gestured control.

Abstract: A method for modeling an object from image data comprises identifying in an image from the video a set of reference points on the object, and, for each reference point identified, observing a displacement of that reference point in response to a motion of the object. The method further comprises grouping together those reference points for which a common translational or rotational motion of the object results in the observed displacement, and fitting the grouped-together reference points to a shape.

Abstract: Systems, methods and computer readable media are disclosed for a localized gesture aggregation. In a system where user movement is captured by a capture device to provide gesture input to the system, demographic information regarding users as well as data corresponding to how those users respectively make various gestures is gathered. When a new user begins to use the system, his demographic information is analyzed to determine a most likely way that he will attempt to make or find it easy to make a given gesture. That most likely way is then used to process the new user's gesture input.

Abstract: Embodiments are disclosed that relate to interacting with a user interface via feedback provided by an avatar. One embodiment provides a method comprising receiving depth data, locating a person in the depth data, and mapping a physical space in front of the person to a screen space of a display device. The method further comprises forming an image of an avatar representing the person, outputting to a display an image of a user interface comprising an interactive user interface control, and outputting to the display device the image of the avatar such that the avatar faces the user interface control. The method further comprises detecting a motion of the person via the depth data, forming an animated representation of the avatar interacting with the user interface control based upon the motion of the person, and outputting the animated representation of the avatar interacting with the control.

Abstract: Embodiments are disclosed that relate to the automatic tagging of recorded content. For example, one disclosed embodiment provides a computing device comprising a processor and memory having instructions executable by the processor to receive input data comprising one or more of a depth data, video data, and directional audio data, identify a content-based input signal in the input data, and apply one or more filters to the input signal to determine whether the input signal comprises a recognized input. Further, if the input signal comprises a recognized input, then the instructions are executable to tag the input data with the contextual tag associated with the recognized input and record the contextual tag with the input data.

Abstract: Automatic depth camera aiming is provided by a method which includes receiving from the depth camera one or more observed depth images of a scene. The method further includes, if a point of interest of a target is found within the scene, determining if the point of interest is within a far range relative to the depth camera. The method further includes, if the point of interest of the target is within the far range, operating the depth camera with a far logic, or if the point of interest of the target is not within the far range, operating the depth camera with a near logic.

Abstract: Systems, methods and computer readable media are disclosed for a gesture tool. A capture device captures user movement and provides corresponding data to a gesture recognizer engine and an application. From that, the data is parsed to determine whether it satisfies one or more gesture filters, each filter corresponding to user-performed gesture. The data and the information about the filters is also sent to a gesture tool, which displays aspects of the data and filters. In response to user input corresponding to a change in a filter, the gesture tool sends an indication of such to the gesture recognizer engine and application, where that change occurs.

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 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: Systems, methods and computer readable media are disclosed for a localized gesture aggregation. In a system where user movement is captured by a capture device to provide gesture input to the system, demographic information regarding users as well as data corresponding to how those users respectively make various gestures is gathered. When a new user begins to use the system, his demographic information is analyzed to determine a most likely way that he will attempt to make or find it easy to make a given gesture. That most likely way is then used to process the new user's gesture input.

Abstract: Systems, methods and computer readable media are disclosed for gesture input beyond skeletal. A user's movement or body position is captured by a capture device of a system. Further, non-user-position data is received by the system, such as controller input by the user, an item that the user is wearing, a prop under the control of the user, or a second user's movement or body position. The system incorporates both the user-position data and the non-user-position data to determine one or more inputs the user made to the system.

Abstract: Systems, methods and computer readable media are disclosed for controlling perspective of a camera-controlled computer. A capture device captures user gestures and sends corresponding data to a recognizer engine. The recognizer engine analyzes the data with a plurality of filters, each filter corresponding to a gesture. Based on the output of those filters, a perspective control is determined, and a display device displays a new perspective corresponding to the perspective control.

Abstract: Systems and methods for mapping natural input devices to legacy system inputs are disclosed. One example system may include a computing device having an algorithmic preprocessing module configured to receive input data containing a natural user input and to identify the natural user input in the input data. The computing device may further include a gesture module coupled to the algorithmic preprocessing module, the gesture module being configured to associate the natural user input to a gesture in a gesture library. The computing device may also include a mapping module to map the gesture to a legacy controller input, and to send the legacy controller input to a legacy system in response to the natural user input.