An image processing method is provided, including: obtaining image data of a cavity wall of an organ; unfolding the cavity wall; and generating an image of the unfolded cavity wall. The unfolding of the cavity wall may include: obtaining a mask and a centerline of the organ; obtaining a connected region of the mask; dividing the connected region into at least one equidistant block; determining an orientation of the equidistant block in a three-dimensional coordinate system including a first direction, a second direction and a third direction; determining an initial normal vector and an initial tangent vector of a center point of the centerline; assigning a projection of the initial normal vector to a normal vector of a light direction of the center point; assigning the third direction or an reverse direction of the third direction to a tangent vector of the light direction of the center point.

Provided are systems and methods for single image-based body animation. An example method includes receiving a input image, the input image including a body of a person, segmenting the input image into a body portion and a background portion, wherein the body portion includes pixels corresponding to the body of the person, fitting a model to the body portion, wherein the model is configured to receive pose parameters representing a pose of the body and generate an output image including an image of the body adopting the pose, receiving a series of further pose parameters, each of the series of further pose parameters representing one of further poses of the body, providing each of the series of further pose parameters to the model to generate a series of output images of the body adopting the further poses, and generating, based on the series of output images, an output video.

There is provided a generation device, an identification information generation method, a reproduction device, and an image generation method capable of easily acquiring a region with a margin and a region with no margin. An identification information generation unit generates margin identification information for identifying that a celestial sphere image includes a region with a margin. A client that uses a margin can easily acquire a region including the margin and a client that does not use a margin can easily acquire a region including no margin. The present technology can be applied to a case in which a celestial sphere image is transmitted from a server and is received and reproduced on a client side.

Provided are systems and methods for processing 360-degree video data by obtaining a 360-degree rectangular formatted projected picture, where the 360-degree rectangular formatted projected picture includes at least a first region, the at least first region includes at least one region boundary, and the at least first region includes a first region area; determining at least one guard band area located within the first region area, where the at least one guard band area is located alongside the at least one region boundary, and the first region area further includes a projected region area located outside the at least one guard band area; and coding a current coding block in the at least one guard band area using at least one additional guard band sample.

A multi-user application system environment engine has an application system that, in turn, includes a simulation engine and a virtualized software environment. The simulation engine runs on top of the virtualized software environment and includes a declaration processor, a scene tree object manager, a viewer, an editor listener, and a rendering processor, coupled to the virtualized software environment, to requisition hardware resources to cause physical manifestation of an instantiated scene tree. The viewer presents to the local user a visual representation of the instantiated scene tree in its current state.

Provided are systems and methods for single image-based body animation. An example method includes receiving a input image, the input image including a body of a person, segmenting the input image into a body portion and a background portion, wherein the body portion includes pixels corresponding to the body of the person, fitting a model to the body portion, wherein the model is configured to receive pose parameters representing a pose of the body and generate an output image including an image of the body adopting the pose, receiving a series of further pose parameters, each of the series of further pose parameters representing one of further poses of the body, providing each of the series of further pose parameters to the model to generate a series of output images of the body adopting the further poses, and generating, based on the series of output images, an output video.

An image processing method is provided, including: obtaining image data of a cavity wall of an organ; unfolding the cavity wall; and generating an image of the unfolded cavity wall. The unfolding of the cavity wall may include: obtaining a mask and a centerline of the organ; obtaining a connected region of the mask; dividing the connected region into at least one equidistant block; determining an orientation of the equidistant block in a three-dimensional coordinate system including a first direction, a second direction and a third direction; determining an initial normal vector and an initial tangent vector of a center point of the centerline; assigning a projection of the initial normal vector to a normal vector of a light direction of the center point; assigning the third direction or an reverse direction of the third direction to a tangent vector of the light direction of the center point.

An embodiment provides for storing, in a server, pipe segment data, e.g., pipe scan data derived from a pipe inspection robot that traversed through an interior of the segment of pipe. The pipe scan data may include three-dimensional (3D) and two-dimensional (2D) image data of the interior of the segment of pipe, where the 2D image data includes a flat graph formed from the 3D image data. In one example, infrastructure summary data is stored in the server, including a level of corrosion and a level of sediment buildup determined based on the pipe scan data. An infrastructure project summary report is based on the infrastructure summary data, and after receiving a request from a client device, the pipe segment data and the infrastructure project summary report are transmitted to the client device.

Methods for creation and use (e.g., for navigation) of displays of flattened (e.g., curvature-straightened) 3-D reconstructions of tissue surfaces, optionally including reconstructions of the interior surfaces of hollow organs. In some embodiments, data comprising a 3-D representation of a tissue surface (for example an interior heart chamber surface) are subject to a geometrical transformation allowing the tissue surface to be presented substantially within a single view of a flattened reconstruction. In some embodiments, a catheter probe in use near the tissue surface is shown in positions that correspond to positions in 3-D space sufficiently to permit navigation; e.g., the probe is shown in flattened reconstruction views nearby view regions corresponding to regions it actually approaches. In some embodiments, automatic and/or easily triggered manual view switching between flattened reconstruction and source reconstruction views is implemented.

The invention relates to a method for identifying individual trees in airborne lidar data and a corresponding computer program product. The method comprises: a. obtaining lidar data points of a group of one or more trees; b. define voxels in a regular 3D grid on the basis of the data points; c. applying an image segmentation algorithm to obtain at least one segment; and, if at least two segments are obtained: d. find the root voxel and branch voxels of a first segment and a second neighbouring segment; and e. merging the first and second segment if the distance between the first and second root voxel is less than a first threshold, the distance between the first root voxel and the closest second branch voxel is less than a second threshold; and the distance between the first branch voxels and the second branch voxels is less than a third threshold.