Models can build three dimensions from two-dimensional images {models for three dimensions from two dimensions}. Stacks of two-dimensional layers can model three-dimensional space. Rotation of one two-dimensional layer can sweep out three-dimensional space.
Mental space has no reading or writing {reading and writing and mental space}, because output becomes input and input becomes output simultaneously and in parallel.
Region boundaries have high contrast. Surfaces have coarser or finer and other texture types. Textures depend on surface slant, surface tilt, object size, object motion, shape constancy, surface smoothness, and reflectance. Segmentation algorithms {segmentation and mental space} separate observed regions by contrast and surface texture. Contrast and steep texture gradients define large domains. Subdomains have different surface textures.
Camera algorithms can use epipolar transform and absolute conic image in Kruppa equation to find standard metric and relative distances and positions {self-calibration and mental space}.
Vision processing can find convexities, concavities, and boundary edges. Later vision processing makes these consistent to build three-dimensional space {shape from shading and mental space}.
Motions cause disparities and disparity rates that can reveal structure {structure from motion and mental space}. Bundle-adjustment algorithm can find three-dimensional scene structure and eye trajectories. First, projective reconstruction can construct the projected structure, and then Euclidean upgrading can find actual shape. Affine projective reconstruction uses Tomasi-Kanade factorization.
Synthesis algorithms {synthesis algorithms} compare vectors and coordinates to build images and space.
Vision algorithms can use fiducials as reference points for calibration to make space coordinates {vision algorithms and space}.
1-Consciousness-Speculations-Space
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Date Modified: 2022.0225