Abstract:
Provided is a method and corresponding apparatus to model a deformable body. The method includes obtaining a material property corresponding to an internal skeletal structure of a deformable body. The method calculates a displacement amount of the skeletal structure according to a motion of the deformable body, based on a boundary condition of the skeletal structure, and the material property. The method further calculates displacement amounts of surface particles on a surface of the deformable body, based on the displacement amount of the skeletal structure, and models the deformable body based on the calculated displacement amounts of the surface particles.
Abstract:
Disclosed is a position estimating method and apparatus that estimates a position based on main sensing data and secondarily determines the position based on the main sensing data and auxiliary sensing data when the auxiliary sensing data is found to be reliable.
Abstract:
A method for generating a three-dimensional (3D) lane model, the method including calculating a free space indicating a driving-allowed area based on a driving image captured from a vehicle camera, generating a dominant plane indicating plane information of a road based on either or both of depth information of the free space and a depth map corresponding to a front of the vehicle, and generating a 3D short-distance road model based on the dominant plane.
Abstract:
Provided is a method and apparatus for modeling a movement of an object that generates a velocity field in a fluid based on a flow of the fluid, selects a vortex model corresponding to the object in the fluid, updates the velocity field based on a velocity variance of the velocity field obtained using the vortex model, and models a movement of the object based on the updated velocity field.
Abstract:
A modeling method searches for a sequence matched to a user input using a fluid animation graph generated based on similarities among frames included in sequences included in the fluid animation graph and models a movement corresponding to the user input based on a result of the searching. Provided also is a corresponding apparatus and a method for preprocessing for such modeling.
Abstract:
Provided is a method of modeling a target object, the method including obtaining information about the target object including an arrangement of particles including target particles, generating coarse particles by down-sampling the target particles, modeling a movement of the target object based on the coarse particles, and redefining the target particles based on a result of the modeling.
Abstract:
Provided are a method and a corresponding apparatus for modeling a deformable body including particles that define a strain energy generated by an external force with respect to a deformable body including particles, and control a displacement of the deformable body based on a volume of the particles corresponding to the displacement of the deformable body, where the displacement is determined based on the strain energy.
Abstract:
An adaptive super sampling method includes: rendering frames of a three-dimensional (3D) model, the frames including a current frame and a previous frame preceding the current frame; determining motion vectors indicating a correspondence relationship between pixels in the current frame and pixels in the previous frame; generating a geometric identifier maps (G-ID maps) respectively corresponding to the current frame and the previous frame based on 3D geometrical properties associated with the pixels in the current frame and the previous frame; based on the motion vectors and the G-ID maps, generating an artifact map predicting where artifacts will occur from inter-frame super sampling of the current frame; and performing adaptive super sampling on the current frame based on the artifact map.
Abstract:
A supersampling method and apparatus are provided. The method includes: receiving a low-resolution three-dimensional (3D) image comprising a current frame and receiving a previous frame preceding the current frame; generating a low-resolution partial image by repeatedly sampling sub-pixel regions of the current frame; warping a high-resolution image, of the previous frame, which has been outputted from a neural network, to a current view corresponding to the current frame; replacing a partial region of the warped high-resolution image of the previous frame with image data from the low-resolution partial image; and generating a high-resolution image of the current frame by applying the high-resolution image of the previous frame, in which the partial region has been replaced, to the neural network.
Abstract:
A method of calculating a depth map includes dividing an input image into segments, calculating reliabilities of the segments, selecting at least one of the segments based on the reliabilities, estimating pose information of a camera with respect to the input image using the selected segment, and calculating a depth map of the input image based on the pose information of the camera.