A device and a method for controlling a device using a real-time image are provided. The method includes: receiving an image captured by an image capturing device connected to a network to display the image in real-time; searching for the device that is connected to the network and is controllable; designating, within the image, a setting zone corresponding to the device; receiving a user input; and controlling the device selected according to the user input. A location of the setting zone within the image may be updated according to a change in the image. The user may receive immediate visual feedback on how the devices are being controlled. The user may control a device displayed on the screen on which the real-time indoor image is displayed without having to navigate through different sub-menus for different devices.

According to an aspect of the present disclosure, there is provided a method of generating training data related to an artificial intelligence-based detection model, which includes the steps of: generating three-dimensional (3D) model of a hidden target object and 3D model of a hiding tool object, respectively, and combining the 3D model of the hidden target object and the 3D model of the hiding tool object; generating a two-dimensional (2D) image by capturing, in at least one direction, the combined 3D model obtained by combining the 3D model of the hidden target object with the 3D model of the hiding tool object; and processing the generated 2D image with reference to deformation or distortion which occurs in a detection target image obtained by actually capturing a detection target object to be detected.

According to an aspect of the present disclosure, there is provided a method of generating training data related to an artificial intelligence-based detection model, which includes the steps of: generating three-dimensional (3D) model of a hidden target object and 3D model of a hiding tool object, respectively, and combining the 3D model of the hidden target object and the 3D model of the hiding tool object; generating a two-dimensional (2D) image by capturing, in at least one direction, the combined 3D model obtained by combining the 3D model of the hidden target object with the 3D model of the hiding tool object; and processing the generated 2D image with reference to deformation or distortion which occurs in a detection target image obtained by actually capturing a detection target object to be detected.

Systems and methods of valve quantification are disclosed. In one embodiment, a method of mitral valve quantification is provided. The method includes generating a 3-D heart model, defining a 3-D mitral valve annulus, fitting a plane through the 3-D mitral valve annulus, measuring the distance between at least two papillary muscle heads, defining an average diameter of at least one cross section around the micro valve annulus, and determining a size of an implant to be implanted.

Systems and methods of valve quantification are disclosed. In one embodiment, a method of mitral valve quantification is provided. The method includes generating a 3-D heart model, defining a 3-D mitral valve annulus, fitting a plane through the 3-D mitral valve annulus, measuring the distance between at least two papillary muscle heads, defining an average diameter of at least one cross section around the micro valve annulus, and determining a size of an implant to be implanted.

A method, apparatus, and system provide the ability to design a convective cooling channel in a computer. Input data is acquired and includes a geometry of an object to be cooled, a design objective, and boundary conditions. Channel designs corresponding to the input data are generated using an iterative topology optimization. One of the channel designs is selected and output.

A method, apparatus, and system provide the ability to design a convective cooling channel in a computer. Input data is acquired and includes a geometry of an object to be cooled, a design objective, and boundary conditions. Channel designs corresponding to the input data are generated using an iterative topology optimization. One of the channel designs is selected and output.

A method for displaying virtual content to a user, the method includes determining an accommodation of the user's eyes. The method also includes delivering, through a first waveguide of a stack of waveguides, light rays having a first wavefront curvature based at least in part on the determined accommodation, wherein the first wavefront curvature corresponds to a focal distance of the determined accommodation. The method further includes delivering, through a second waveguide of the stack of waveguides, light rays having a second wavefront curvature, the second wavefront curvature associated with a predetermined margin of the focal distance of the determined accommodation.

A method for displaying virtual content to a user, the method includes determining an accommodation of the user's eyes. The method also includes delivering, through a first waveguide of a stack of waveguides, light rays having a first wavefront curvature based at least in part on the determined accommodation, wherein the first wavefront curvature corresponds to a focal distance of the determined accommodation. The method further includes delivering, through a second waveguide of the stack of waveguides, light rays having a second wavefront curvature, the second wavefront curvature associated with a predetermined margin of the focal distance of the determined accommodation.

The present disclosure describes techniques of rendering images using explicit object representation via rays tracing volume density aggregation. The techniques comprise reconstructing an object into a plurality of Gaussian ellipsoids; determining a volume density of each of the plurality of Gaussian ellipsoids along each of a plurality of viewing rays; determining a weight of each of the plurality of Gaussian ellipsoids based on the volume density; and synthesizing an image of the object using the determined weight on each pixel of the image to interpolate attributes of each of the plurality of Gaussian ellipsoids.