Shape from Shading. II. Geodesic Bisection and Alignment

Perception ◽  
1994 ◽  
Vol 23 (2) ◽  
pp. 191-200 ◽  
Author(s):  
Alan Johnston ◽  
Peter J Passmore
Keyword(s):  
Visual System ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Shape From Shading ◽  
Surface Orientation ◽  
Surface Shape ◽  
Ray Casting ◽  
Arc Length ◽  
Spatial Environment ◽  
Spatial Judgment

Pattern-acuity tasks have provided valuable information about the precision with which the visual system can make judgments about relative spatial position in two-dimensional images. However, outside the laboratory the visual system is habitually faced with the more difficult task of making positional judgments within a three-dimensional spatial environment. Thus our perceptual systems for representing surface shape also need to support the recovery of the location and disposition of features in a three-dimensional space. An investigation of the precision of three-dimensional position judgments in two spatial-judgment tasks, arc length bisection along geodesics and geodesic alignment, is reported. The spatial-judgment tasks were defined with reference to a sphere rendered by means of ray-casting techniques. The presence of shading and texture cues had no effect on discrimination thresholds in either task. Observers' constant errors were generally less than the just noticeable distance, demonstrating that the observers can perform these positional judgment tasks without substantial bias. It is argued that there is no explicit computation of arc length on the basis of shading and texture information and that surface-orientation information cannot be used as a reference in geodesic-alignment tasks. The results raise questions about the utility of a representation of surface orientation in the human visual system.

Shape from Shading. I: Surface Curvature and Orientation

Perception ◽  
1994 ◽  
Vol 23 (2) ◽  
pp. 169-189 ◽  
Author(s):  
Alan Johnston ◽  
Peter J Passmore
Keyword(s):  
Visual System ◽  
Light Source ◽  
Human Visual System ◽  
Three Dimensional ◽  
Shape Index ◽  
Shape From Shading ◽  
Surface Curvature ◽  
Surface Shape ◽  
Alignment Task ◽  
Band Limited

The human visual system makes effective use of shading alone in recovering the shape of objects. Pictures of sculptures are readily interpreted—a situation where shading provides virtually the sole cue to shape. However, shading has been considered a poor cue to depth in comparison with retinal disparity and kinetic cues. Curvature discrimination thresholds were measured with the use of a surface-alignment task for a range of surface curvatures from 0.16 cm−1 to 1.06 cm−1. Weber fractions were around 0.1, demonstrating considerable precision in this task. Weber fractions did not vary substantially as a function of surface curvature. Rotation of the light source around the line of sight had no effect on curvature discrimination but rotation towards the viewer increased discrimination thresholds. In contrast, slant discrimination declined with rotation of the light-source vector towards the viewpoint. When a band-limited random grey-level texture was mapped onto the sphere, curvature discrimination thresholds increased gradually as a function of texture contrast, even though texture and shading provided consistent cues to depth. Adding texture also increased slant discrimination thresholds, demonstrating that texture can act as a source of noise in shape-from-shading tasks. The psychophysical findings have been used to evaluate whether current algorithms for shape from shading in computer vision could serve as models of human three-dimensional shape analysis and to highlight low-level intramodular interactions between depth cues. It is demonstrated that, in the case of surfaces defined by shading, curvature descriptions are primary and do not depend upon the prior encoding of surface orientation, and Koenderink's local-shape index is suggested as an alternative intermediate representation of surface shape in the human visual system.

Spatial phenomenology requires potential illumination

2003 ◽  
Vol 26 (4) ◽  
pp. 425-426
Author(s):  
James A. Schirillo
Keyword(s):  
Visual System ◽  
Spatial Model ◽  
Dimensional Space ◽  
Color Constancy ◽  
Three Dimensional ◽  
Two Dimensions ◽  
Three Dimensional Space

Collapsing three-dimensional space into two violates Lehar's “volumetric mapping” constraint and can cause the visual system to construct illusory transparent regions to replace voxels that would have contained illumination. This may underlie why color constancy is worse in two dimensions, and argues for Lehar to revise his phenomenal spatial model by putting “potential illumination” in empty space.

Statistical Approach to Shape from Shading: Reconstruction of Three-Dimensional Face Surfaces from Single Two-Dimensional Images

1996 ◽  
Vol 8 (6) ◽  
pp. 1321-1340 ◽  
Author(s):  
Joseph J. Atick ◽  
Paul A. Griffin ◽  
A. Norman Redlich
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Practical Interest ◽  
Principal Component ◽  
Shape From Shading ◽  
Shape Space ◽  
Two Dimensional ◽  
Two Dimensional Image ◽  
Low Dimensional ◽  
Dimensional Object

The human visual system is proficient in perceiving three-dimensional shape from the shading patterns in a two-dimensional image. How it does this is not well understood and continues to be a question of fundamental and practical interest. In this paper we present a new quantitative approach to shape-from-shading that may provide some answers. We suggest that the brain, through evolution or prior experience, has discovered that objects can be classified into lower-dimensional object-classes as to their shape. Extraction of shape from shading is then equivalent to the much simpler problem of parameter estimation in a low-dimensional space. We carry out this proposal for an important class of three-dimensional (3D) objects: human heads. From an ensemble of several hundred laser-scanned 3D heads, we use principal component analysis to derive a low-dimensional parameterization of head shape space. An algorithm for solving shape-from-shading using this representation is presented. It works well even on real images where it is able to recover the 3D surface for a given person, maintaining facial detail and identity, from a single 2D image of his face. This algorithm has applications in face recognition and animation.

A Measurement of the Adaptation of Color Vision to the Spectral Environment

1997 ◽  
Vol 8 (2) ◽  
pp. 130-134 ◽  
Author(s):  
Steven M. Boker
Keyword(s):  
Maximum Likelihood ◽  
Visual System ◽  
Goodness Of Fit ◽  
Factor Model ◽  
Dimensional Space ◽  
Color Space ◽  
Three Dimensional ◽  
Color Matching ◽  
Four Dimensions ◽  
Unconstrained Model

An exploratory factor analysis of the reflectance spectral distributions of a sample of natural and man-made objects yields a factor pattern remarkably similar to psychophysical color-matching curves. The goodness-of-fit indices from a maximum likelihood confirmatory factor model with fixed factor loadings specified by empirical trichromatic color-matching data indicate that the human visual system performs near to an optimum value for an ideal trichromatic system composed of three linear components. An unconstrained four-factor maximum likelihood model fits significantly better than a three-factor unconstrained model, suggesting that a color metric is better represented in four dimensions than in a three-dimensional space. This fourth factor can be calculated as a nonlinear interaction term between the first three factors: thus, a trichromatic input is sufficient to compute a color space of four dimensions. The visual system may exploit this nonlinear dependency in the spectral environment in order to obtain a four-dimensional color space without the biological cost of a fourth color receptor.

scholarly journals Mannheim Offsets of Ruled Surfaces

2009 ◽  
Vol 2009 ◽  
pp. 1-9 ◽  
Author(s):  
Keziban Orbay ◽  
Emin Kasap ◽  
İsmail Aydemir
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Geodesic Curvature ◽  
Ruled Surface ◽  
Ruled Surfaces ◽  
Arc Length ◽  
Spherical Indicatrix ◽  
Constant Distance ◽  
Mannheim Offset ◽  
Three Dimensional Space

In a recent works Liu and Wang (2008; 2007) study the Mannheim partner curves in the three dimensional space. In this paper, we extend the theory of the Mannheim curves to ruled surfaces and define two ruled surfaces which are offset in the sense of Mannheim. It is shown that, every developable ruled surface have a Mannheim offset if and only if an equation should be satisfied between the geodesic curvature and the arc-length of spherical indicatrix of it. Moreover, we obtain that the Mannheim offset of developable ruled surface is constant distance from it. Finally, examples are also given.

How does our visual system interpret the color of light filled in a three-dimensional space?

2002 ◽  
Author(s):  
Naohiro Toda ◽  
Taiichiro Ishida
Keyword(s):  
Visual System ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Three Dimensional Space

Localization Algorithm for Three-Dimensional Space of Building Based on ZigBee Wireless Networks

2014 ◽  
Vol 926-930 ◽  
pp. 1546-1549
Author(s):  
Yun Hong Liu ◽  
Tong Wei Niu
Keyword(s):  
Wireless Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Signal Strength ◽  
High Accuracy ◽  
Localization Algorithm ◽  
Received Signal Strength Indicator ◽  
Spatial Environment ◽  
The Impact ◽  
Three Dimensional Space

ZigBee wireless networks can be used for locating the objects monitored inside the building, in which the location method based on RSSI (Received Signal Strength Indicator) has a broad range of application. For the complex spatial environment of the building, a three-dimensional localization algorithm will be proposed in this paper which can achieve high accuracy of location, meanwhile mitigate the impact of the RSSI error on the location results efficiently. This method is applicable to the NLOS environment in condition of multi-barrier.

Unifying shading and texture through an active observer

1989 ◽  
Vol 238 (1290) ◽  
pp. 25-37 ◽  
Keyword(s):  
Three Dimensional ◽  
Shape From Shading ◽  
Surface Orientation ◽  
The Other ◽  
Simple Solution ◽  
Image Intensity ◽  
Other Hand ◽  
Shape From Texture ◽  
Perceptual Phenomenon

Shading (variations of image intensity) provides an important cue for understanding the shape of three-dimensional surfaces from monocular views. On the other hand, texture (distribution of discontinuities on the surface) is a strong cue for recovering surface orientation by using mon­ocular images. But given the image of an object or scene, what tech­nique should we use to recover the shape of what is imaged ? Resolution of shape from shading requires knowledge of the reflectance of the imaged surface and, usually, the fact that it is smooth (i. e. it shows no disconti­nuities). Determination of shape from texture requires knowledge of the distribution of surface markings (i. e. discontinuities). One might expect that one method would work when the other does not. I present a theory on how an active observer can determine shape from the image of an object or scene regardless of whether the image is shaded, textured, or both, and without any knowledge of reflectance maps or the distri­bution of surface markings. The approach is successful because the active observer is able to manipulate the constraints behind the perceptual phenomenon at hand and thus derive a simple solution. Several experi­mental results are presented with real and synthetic images.

Three Dimensional structure and organization of diploid chromosomes by optical section microscopy

1987 ◽  
Vol 45 ◽  
pp. 633-635
Author(s):  
David A. Agard ◽  
Yasushi Hiraoka ◽  
John W. Sedat
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Developmental State ◽  
Mitotic Cell ◽  
Biological Properties ◽  
Dimensional Structure ◽  
Specific Gene ◽  
Three Dimensional Structure ◽  
Complementary Techniques ◽  
Dynamic Structures

In an effort to understand the complex relationship between structure and biological function within the nucleus, we have embarked on a program to examine the three-dimensional structure and organization of Drosophila melanogaster embryonic chromosomes. Our overall goal is to determine how DNA and proteins are organized into complex and highly dynamic structures (chromosomes) and how these chromosomes are arranged in three dimensional space within the cell nucleus. Futher, we hope to be able to correlate structual data with such fundamental biological properties as stage in the mitotic cell cycle, developmental state and transcription at specific gene loci.Towards this end, we have been developing methodologies for the three-dimensional analysis of non-crystalline biological specimens using optical and electron microscopy. We feel that the combination of these two complementary techniques allows an unprecedented look at the structural organization of cellular components ranging in size from 100A to 100 microns.

Diffraction contrast of dislocations in icosahedral quasicrystals

1990 ◽  
Vol 48 (4) ◽  
pp. 454-455
Author(s):  
K. Urban ◽  
Z. Zhang ◽  
M. Wollgarten ◽  
D. Gratias
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Complete Characterization ◽  
Extinction Condition ◽  
Burgers Vector ◽  
Diffraction Contrast ◽  
Lattice Geometry ◽  
Reference Space ◽  
Icosahedral Quasicrystals ◽  
The One

Recently dislocations have been observed by electron microscopy in the icosahedral quasicrystalline (IQ) phase of Al65Cu20Fe15. These dislocations exhibit diffraction contrast similar to that known for dislocations in conventional crystals. The contrast becomes extinct for certain diffraction vectors g. In the following the basis of electron diffraction contrast of dislocations in the IQ phase is described. Taking account of the six-dimensional nature of the Burgers vector a “strong” and a “weak” extinction condition are found.Dislocations in quasicrystals canot be described on the basis of simple shear or insertion of a lattice plane only. In order to achieve a complete characterization of these dislocations it is advantageous to make use of the one to one correspondence of the lattice geometry in our three-dimensional space (R3) and that in the six-dimensional reference space (R6) where full periodicity is recovered . Therefore the contrast extinction condition has to be written as gpbp + gobo = 0 (1). The diffraction vector g and the Burgers vector b decompose into two vectors gp, bp and go, bo in, respectively, the physical and the orthogonal three-dimensional sub-spaces of R6.

Sign in / Sign up

Export Citation Format

Share Document