Search results
Results from the WOW.Com Content Network
Z-buffer data. A depth buffer, also known as a z-buffer, is a type of data buffer used in computer graphics to represent depth information of objects in 3D space from a particular perspective. The depth is stored as a height map of the scene, the values representing a distance to camera, with 0 being the closest.
The SSIM index is a full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as reference. SSIM is a perception -based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual ...
In 3D computer graphics and computer vision, a depth map is an image or image channel that contains information relating to the distance of the surfaces of scene objects from a viewpoint. The term is related (and may be analogous) to depth buffer , Z-buffer , Z-buffering , and Z-depth . [ 1 ]
Depth perception is the ability to perceive distance to objects in the world using the visual system and visual perception. It is a major factor in perceiving the world in three dimensions . Depth sensation is the corresponding term for non-human animals, since although it is known that they can sense the distance of an object, it is not known ...
Maze generation animation using Wilson's algorithm (gray represents an ongoing random walk). Once built the maze is solved using depth first search. All the above algorithms have biases of various sorts: depth-first search is biased toward long corridors, while Kruskal's/Prim's algorithms are biased toward many short dead ends.
Figure 2. Simulation of disparity from depth in the plane. (relates to Figure 1) Brain cells in a part of the brain responsible for processing visual information coming from the retinae (primary visual cortex) can detect the existence of disparity in their input from the eyes.
All together, an iterative deepening search from depth all the way down to depth expands only about % more nodes than a single breadth-first or depth-limited search to depth , when =. [ 4 ] The higher the branching factor, the lower the overhead of repeatedly expanded states, [ 1 ] : 6 but even when the branching factor is 2, iterative ...
A simple example is fitting a line in two dimensions to a set of observations. Assuming that this set contains both inliers, i.e., points which approximately can be fitted to a line, and outliers, points which cannot be fitted to this line, a simple least squares method for line fitting will generally produce a line with a bad fit to the data including inliers and outliers.