Abstract: Systems, methods and computer readable media are disclosed for a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.

Abstract: Systems, methods and computer readable media are disclosed for manipulating virtual objects. A user may utilize a controller, such as his hand, in physical space to associate with a cursor in a virtual environment. As the user manipulates the controller in physical space, this is captured by a depth camera. The image data from the depth camera is parsed to determine how the controller is manipulated, and a corresponding manipulation of the cursor is performed in virtual space. Where the cursor interacts with a virtual object in the virtual space, that virtual object is manipulated by the cursor.

Abstract: Various embodiments relating to detecting a conversation during presentation of content on a computing device, and taking one or more actions in response to detecting the conversation, are disclosed. In one example, an audio data stream is received from one or more sensors, a conversation between a first user and a second user is detected based on the audio data stream, and presentation of a digital content item is modified by the computing device in response to detecting the conversation.

Abstract: Various embodiments relating to detecting at least one of conversation, the presence and the identity of others during presentation of digital content on a computing device. When another person is detected, one or more actions may be taken with respect to the digital content. For example, the digital content may be minimized, moved, resized or otherwise modified.

Abstract: Systems, methods and computer readable media are disclosed for a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.

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 a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.

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 a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.

Abstract: Systems, methods and computer readable media are disclosed for a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.

Abstract: Systems, methods and computer readable media are disclosed for a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.

Abstract: Systems, methods and computer readable media are disclosed for a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.

Abstract: Systems, methods and computer readable media are disclosed for a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.

Abstract: Disclosed herein are systems and methods for decorating a display environment. In one embodiment, a user may decorate a display environment by making one or more gestures, using voice commands, using a suitable interface device, and/or combinations thereof. A voice command can be detected for user selection of an artistic feature, such as, for example, a color, a texture, an object, and a visual effect for decorating in a display environment. The user can also gesture for selecting a portion of the display environment for decoration. Next, the selected portion of the display environment can be altered based on the selected artistic feature. The user's motions can be reflected in the display environment by an avatar. In addition, a virtual canvas or three-dimensional object can be displayed in the display environment for decoration by the user.

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: Disclosed herein are systems and methods for altering a view perspective within a display environment. For example, gesture data corresponding to a plurality of inputs may be stored. The input may be input into a game or application implemented by a computing device. Images of a user of the game or application may be captured. For example, a suitable capture device may capture several images of the user over a period of time. The images may be analyzed and processed for detecting a user's gesture. Aspects of the user's gesture may be compared to the stored gesture data for determining an intended gesture input for the user. The comparison may be part of an analysis for determining inputs corresponding to the gesture data, where one or more of the inputs are input into the game or application and cause a view perspective within the display environment to be altered.

Abstract: Systems, methods and computer readable media are disclosed for manipulating virtual objects. A user may utilize a controller, such as his hand, in physical space to associate with a cursor in a virtual environment. As the user manipulates the controller in physical space, this is captured by a depth camera. The image data from the depth camera is parsed to determine how the controller is manipulated, and a corresponding manipulation of the cursor is performed in virtual space. Where the cursor interacts with a virtual object in the virtual space, that virtual object is manipulated by the cursor.

Abstract: Systems, methods and computer readable media are disclosed for a gesture recognizer system architecture. A recognizer engine is provided, which receives user motion data and provides that data to a plurality of filters. A filter corresponds to a gesture, that may then be tuned by an application receiving information from the gesture recognizer so that the specific parameters of the gesture—such as an arm acceleration for a throwing gesture—may be set on a per-application level, or multiple times within a single application. Each filter may output to an application using it a confidence level that the corresponding gesture occurred, as well as further details about the user motion data.