Abstract: A management system for managing data rebalancing in a storage system that has a plurality of nodes configured to control input and output of data for a storage device that is a control target, and redundantly stores and manages predetermined data units in a plurality of storage devices includes a processor unit.

Abstract: Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or “AR selfies.” In an embodiment, a method comprises: capturing, by a first camera of a mobile device, live image data, the live image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Abstract: Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or “AR selfies.” In an embodiment, a method comprises: capturing, by a first camera of a mobile device, live image data, the live image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Abstract: Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or “AR selfies.” In an embodiment, a method comprises: capturing, by a first camera of a mobile device, image data, the image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Abstract: Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or “AR selfies.” In an embodiment, a method comprises: capturing, by a first camera of a mobile device, live image data, the live image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Abstract: Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or “AR selfies.” In an embodiment, a method comprises: capturing, by a first camera of a mobile device, image data, the image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Abstract: In some implementations, a computing device can track an object from a first image frame to a second image frame using a self-correcting tracking method. The computing device can select points of interest in the first image frame. The computing device can track the selected points of interest from the first image frame to the second image frame using optical flow object tracking. The computing device can prune the matching pairs of points and generate a transform based on the remaining matching pairs to detect the selected object in the second image frame. The computing device can generate a tracking confidence metric based on a projection error for each point of interest tracked from the first frame to the second frame. The computing device can correct tracking errors by reacquiring the object when the tracking confidence metric is below a threshold value.

Abstract: In some implementations, a computing device can track an object from a first image frame to a second image frame using a self-correcting tracking method. The computing device can select points of interest in the first image frame. The computing device can track the selected points of interest from the first image frame to the second image frame using optical flow object tracking. The computing device can prune the matching pairs of points and generate a transform based on the remaining matching pairs to detect the selected object in the second image frame. The computing device can generate a tracking confidence metric based on a projection error for each point of interest tracked from the first frame to the second frame. The computing device can correct tracking errors by reacquiring the object when the tracking confidence metric is below a threshold value.

Abstract: Some embodiments provide a program that provides a graphical user interface (GUI). The GUI includes a display area for displaying an image that includes several pixels. Each pixel includes a set of color component values. The GUI includes a waveform monitor for displaying a graph that includes several graphical representations of the several pixels in the image. Each graphical representation is (1) plotted along a first axis of the graph based on a position of a corresponding pixel in the image and (2) plotted along a second axis of the graph based on the set of color component values of the corresponding pixel in the image. A color of each graphical representation is similar to a color of the corresponding pixel that is used for displaying the pixel in the display area.

Abstract: Embodiments of noise reduction systems and methods are disclosed. One method embodiment, among others, comprises transforming a residual signal to produce transform coefficients, and applying the transform coefficients to a quantization matrix and a configurable gain matrix to provide a frequency-selective weighting of the transform coefficients having a gain that is sensitive to noise levels.

Abstract: To provide a fuel cell power generation system which has no assist combustion system and thus is simple in structure and a method for starting the fuel cell power generation system and controlling the operation of the fuel cell power generation system, in order to provide a fuel cell power generation system which operates stably with a high reliability.