Abstract:
A method comprises receiving one or more depth images from a depth camera, the depth images indicating a depth of a surface imaged by each pixel of the depth images. The method may further comprise identifying a human subject imaged by the depth images and recognizing within one or more of the depth images a beacon emitted from a control device. A position of the control device may be assessed in three dimensions, and the control device may be associated with the human subject based on a proximity of the control device to the human subject or other parameter of the control device with relation to the human subject.
Abstract:
An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may also be removed to isolate one or more voxels associated with a foreground object such as a human target. A location or position of one or more extremities of the isolated human target may then be determined.
Abstract:
A computing system such as a game console maintains and updates a biometric profile of a user. In one aspect, biometric data of the user is continuously obtained from a sensor such as an infrared and visible light camera, and used to update the biometric profile using a machine learning process. In another aspect, a user is prompted to confirm his or her identify when multiple users are detected at the same time and/or when the user is detected with a confidence level which is below a threshold. A real-time image of the user being identified can be displayed on a user interface with user images associated with one or more accounts. In another aspect, the biometric profile is managed by a shell on the computing system, where the shell makes the biometric profile available to any of a number of applications on the computing system.
Abstract:
A method for estimating a metabolic equivalent of task for use with a computing device is provided herein. The method includes receiving input from a capture device of a user; and tracking a position of each of the plurality of joints of the user. The method further includes determining a distance traveled for each of the plurality of joints between a first frame and a second frame; and calculating a horizontal velocity and a vertical velocity for each of the plurality of joints based on the distance traveled and an elapsed time between the first and second frames. The method further includes estimating a value for the metabolic equivalent of task using a metabolic equation including a component for the horizontal velocity and a component for the vertical velocity for each of the plurality of joints; and outputting the value for display.
Abstract:
A system and method are disclosed for tracking image and audio data over time to automatically identify a person based on a correlation of their voice with their body in a multi-user game or multimedia setting.
Abstract translation:公开了一种系统和方法,用于随着时间的推移跟踪图像和音频数据,以基于他们的语音与他们的身体在多用户游戏或多媒体设置中的相关性来自动识别人。 p >
Abstract:
An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may also be removed to isolate one or more voxels associated with a foreground object such as a human target. A location or position of one or more extremities of the isolated human target may be determined and a model may be adjusted based on the location or position of the one or more extremities.
Abstract:
A method comprises detecting a control device, and if the control device is not bound to the computing system, detecting an optical beacon emitted from the control device and binding the control device to the computing system.
Abstract:
Methods for face recognition are provided. In one example, a method for face recognition includes receiving a user image and detecting a user luminance of data representing the user's face. An adaptive low pass filter is selected that corresponds to the user luminance of the user's face. The filter is applied to the user image to create a filtered user image. The filtered user image is projected to create a filtered user image representation. A filtered reference image representation that has been filtered with the same low pass filter is selected from a reference image database. The method then determines whether the filtered reference image representation matches the filtered user image representation.
Abstract:
Embodiments are disclosed herein that relate to the use of active tag codes that change as a function of time to incorporate a greater amount of data into the tag code compared to a static tag code of similar configuration. For example, one disclosed embodiment provides a method of presenting an active tag code to a receiving device. The method includes presenting a first portion of the active tag code at a first time, the first portion of the active tag code encoding a first subset of information of a set of information encoded in the active tag code. The method further includes presenting a second portion of the active tag code at a second, later time, the second portion of the active tag code encoding a second subset of information of the set of information encoded in the active tag code.
Abstract:
A control device includes a housing. The control device also includes a wireless communicator interior the housing. The wireless communicator wirelessly sends commands for controlling an electronic device, such as a game console. The control device also includes a reflector positioned to reflect light directed at the housing.