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See searches and references containing SIGNED DISTANCE-FUNCTION!SIGNED DISTANCE-FUNCTION
Distance from a point to the boundary of a set
mathematics and its applications, the signed distance function or signed distance field (SDF) is the orthogonal distance of a given point x to the boundary
Signed_distance_function
Separation between two points
-38° A distance: 8.72 km In mathematics and its applications, the signed distance function or signed distance field (SDF) is the orthogonal distance of a
Distance
3D computer graphics rendering method
point is approximated between the ray and a surface defined by a signed distance function (SDF). The SDF is evaluated for each iteration in order to be able
Ray_marching
Derived representation of a digital image
marching cubes algorithm. Signed distance function Function representation Parallel curve Level sets methods for distance computation. Gibson, Sarah
Distance_transform
Mathematical space with a notion of distance
together with a notion of distance between its points. The distance is measured by a function called a metric or distance function. Metric spaces are a general
Metric_space
Topics referred to by the same term
Scientific Data Format, a Hierarchical Data Format implementation Signed distance function (or field), in mathematical applications Syntax Definition Formalism
SDF
Type of artificial neural network
dynamic cases. For example, a neural field can learn signed distance functions (SDFs) or occupancy functions, which provide an efficient and continuous representation
Neural_field
Topics referred to by the same term
Forensics, an academic degree Multi-channel signed distance field, a field created by a signed distance function Danish company "Møbler Samling Drømmen Flyder"
MSDF
Line or vector perpendicular to a curve or a surface
stereo. The normal vector may be obtained as the gradient of the signed distance function. The normal ray is the outward-pointing ray perpendicular to the
Normal_(geometry)
Distance along a curve
point taken as origin in the curve (see also: curve orientation and signed distance). If a planar curve in R 2 {\displaystyle \mathbb {R} ^{2}} is defined
Arc_length
Surface in 3D space defined by an implicit function of three variables
implicit surfaces. Implicit curve Geologic modelling Signed distance function Radial basis function Adriano N. Raposo; Abel J.P. Gomes (2019). "Pi-surfaces:
Implicit_surface
Rendering method
intersection point between the ray and a surface defined by a signed distance function (SDF). The SDF is evaluated for each iteration in order to be able
Ray_tracing_(graphics)
Image-based volume rendering technique
point is approximated between the ray and a surface defined by a signed distance function (SDF). The SDF is evaluated for each iteration in order to be able
Volume_ray_casting
Mathematical idealization of the surface of a body
Perimeter, a two-dimensional equivalent Polyhedral surface Shape Signed distance function Solid figure Surface area Surface patch Surface integral A smooth
Surface_(mathematics)
modeling Isosurface Signed distance function HyperFun Digital materialization ""Shape Modeling and Computer Graphics with Real Functions"". Archived from
Function_representation
Generalization of the concept of parallel lines
S_{d}^{-1}=S^{-1}+S_{n}^{-1}} . Bump mapping Channel surface Distance function and signed distance function Distance field Offset printing Tubular neighborhood Willson
Parallel_curve
Distance from origin of tangent hyperplanes
mathematics, the support function hA of a non-empty closed convex set A in R n {\displaystyle \mathbb {R} ^{n}} describes the (signed) distances of supporting hyperplanes
Support_function
Generalized notion of measure in mathematics
signed measure is a generalization of the concept of (positive) measure by allowing the set function to take negative values, i.e., to acquire sign.
Signed_measure
Number property of being positive or negative
Percent sign Plus–minus sign Positive element Signedness Symmetry in mathematics Weisstein, Eric W. "Sign". mathworld.wolfram.com. Retrieved 2020-08-26
Sign_(mathematics)
Distance between two statistical objects
to "distance", similar terms include deviance, deviation, discrepancy, discrimination, and divergence, as well as others such as contrast function and
Statistical_distance
Solution to partial differential equation
known to be the signed distance function to the boundary of the domain. Note also in the previous example, the importance of the sign of F {\displaystyle
Viscosity_solution
Producing images of 3D scenes
object, such as a volumetric dataset or a surface defined by a signed distance function. It is not, by itself, a rendering method, but it can be incorporated
Rendering_(computer_graphics)
Programming language for creating 3D printable products
modifications while modifying the script. ShapeJS uses a combination of signed distance functions and voxel representations. A voxel is similar to a 2D pixel but
ShapeJS
Measure of linear correlation
cross-product of standardized variables Function of the angle between two standardized regression lines Function of the angle between two variable vectors
Pearson correlation coefficient
Pearson_correlation_coefficient
Length of a line segment
given distance from a given point) as its neighborhoods. Other common distances in real coordinate spaces and function spaces: Chebyshev distance (L∞ distance)
Euclidean_distance
Function related to statistics and probability theory
A likelihood function (often simply called the likelihood) measures how well a statistical model explains observed data by calculating the probability
Likelihood_function
Mathematical relation assigning a probability event to a cost
optimization and decision theory, a loss function or cost function (sometimes also called an error function) is a function that maps an event or values of one
Loss_function
Mathematical functions
In mathematics, the lemniscate elliptic functions are elliptic functions related to the arc length of the lemniscate of Bernoulli. They were first studied
Lemniscate_elliptic_functions
Mathematical function for the probability a given outcome occurs in an experiment
often described by functions such as cumulative distribution functions, probability mass functions, or probability density functions. Which description
Probability_distribution
Frequency with which an engineered system or component fails
function), h ( t ) {\displaystyle h(t)} . In the many-system case, this is defined as the proportional failure rate of the systems still functioning at
Failure_rate
Description of particle density in statistical mechanics
(atoms, molecules, colloids, etc.), describes how density varies as a function of distance from a reference particle. If a given particle is taken to be at
Radial_distribution_function
Covariance and correlation
processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. This is also known as
Cross-correlation
Measure of the asymmetry of random variables
} where Q is the quantile function (i.e., the inverse of the cumulative distribution function). The numerator is difference between the
Skewness
Point to which functions converge in analysis
mathematics, the limit of a function is a fundamental concept in calculus and analysis concerning the behavior of that function near a particular input which
Limit_of_a_function
Mathematical function
In mathematics, a Gaussian function, often simply referred to as a Gaussian, is a function of the base form f ( x ) = exp ( − x 2 ) {\displaystyle f(x)=\exp(-x^{2})}
Gaussian_function
Measure of covariance of components of a random vector
functions, the map shows statistical relations between different regions of the random functions. Statistically independent regions of the functions show
Covariance_matrix
Functions of an angle
mathematics, the trigonometric functions (also called circular functions, angle functions or goniometric functions) are real functions which relate an angle of
Trigonometric_functions
Computer vision framework
wavefront, which defines an additional speed function. Accordingly, then the evolution of the signed distance function ϕ t ( x ) {\displaystyle \textstyle \phi
Gradient_vector_flow
Distance function defined between probability distributions
In mathematics, the Wasserstein distance or Kantorovich–Rubinstein metric is a distance function defined between probability distributions on a given metric
Wasserstein_metric
Measure of the shape of a function
Moments of a function in mathematics are certain quantitative measures related to the shape of the function's graph. For example, if the function represents
Moment_(mathematics)
Self-shadowing Shader Shading Shading language Shadow mapping Shadow volume Signed distance function Simplex noise Simulation noise Skeletal animation Slab method Soft-body
List of computer graphics and descriptive geometry topics
List_of_computer_graphics_and_descriptive_geometry_topics
Correlation of a signal with a time-shifted copy of itself, as a function of shift
Pearson correlation between values of the process at different times, as a function of the two times or of the time lag. Let { X t } {\displaystyle \left\{X_{t}\right\}}
Autocorrelation
Mathematical function with no sudden changes
In mathematics, a continuous function is a function such that a small variation of its argument induces at most a small variation of its value. This implies
Continuous_function
Branch of mathematics
steady 50 mph for 3 hours results in a total distance of 150 miles. Plotting the velocity as a function of time yields a rectangle with a height equal
Calculus
Conjecture on zeros of the zeta function
Unsolved problem in mathematics Do all non-trivial zeros of the Riemann zeta function have a real part equal to one half? More unsolved problems in mathematics
Riemann_hypothesis
Cosmological formulas for expanding universe
Distance measures are used in physical cosmology to generalize the concept of distance between two objects or events in an expanding universe. They may
Distance_measure
Statistical test comparing two probability distributions
statistic quantifies a distance between the empirical distribution function of the sample and the cumulative distribution function of the reference distribution
Kolmogorov–Smirnov_test
Value approached by a mathematical object
{\displaystyle x_{i}} are real, an example of a suitable distance function is the Euclidean distance, defined by d ( x , y ) = ‖ x − y ‖ = ∑ i ( x i − y i
Limit_(mathematics)
their function. France is a signatory to the 1968 Vienna Convention on Road Signs and Signals. France signed the Vienna Convention on Road Signs and Signals
Road_signs_in_France
Distance from zero to a number
numbers (their absolute difference) is the distance between them. The notion of an abstract distance function in mathematics can be seen to be a generalisation
Absolute_value
Analytic function in mathematics
The Riemann zeta function or Euler–Riemann zeta function, denoted by the lowercase Greek letter ζ (zeta), is a mathematical function of a complex variable
Riemann_zeta_function
Probability of survival beyond any specified time
certain time. The survival function is also known as the survivor function or reliability function. The term reliability function is common in engineering
Survival_function
Multivalued function in mathematics
In mathematics, the Lambert W function, also called the omega function or product logarithm, is a multivalued function, namely the branches of the converse
Lambert_W_function
Statistical measure of variability
data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily
Median_absolute_deviation
Measure of the joint variability
Analysis of covariance Autocovariance Covariance function Covariance matrix Covariance operator Distance covariance, or Brownian covariance. Law of total
Covariance
Generates a forecast of future values of a time series
exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign
Exponential_smoothing
Statistical hypothesis test
function. SciPy includes an implementation of the Wilcoxon signed-rank test in Python. Accord.NET includes an implementation of the Wilcoxon signed-rank
Wilcoxon_signed-rank_test
Nonparametric test of the null hypothesis
Nonparametric tests used on two dependent samples are the sign test and the Wilcoxon signed-rank test. Henry Mann and Donald Ransom Whitney developed
Mann–Whitney_U_test
Type of average of a collection of numbers
and redefine the difference as a modular distance (i.e. the distance on the circle: so the modular distance between 1° and 359° is 2°, not 358°). The
Arithmetic_mean
Absolute value: distance to the origin (zero point) Sigma function: Sums of powers of divisors of a given natural number. Euler's totient function: Number of
List of mathematical functions
List_of_mathematical_functions
Value that appears most often in a set of data
random variable, the mode is the value x at which the probability mass function P(X) takes its maximum value, i.e., x = argmaxxi P(X = xi). In other words
Mode_(statistics)
Motion of a curve based on its curvature
Steven; Tsai, Richard (2010), "Diffusion generated motion using signed distance functions" (PDF), Journal of Computational Physics, 229 (4): 1017–1042,
Curve-shortening_flow
Measure of distance between two proportions
In statistics, Cohen's h, popularized by Jacob Cohen, is a measure of distance between two proportions or probabilities. Cohen's h has several related
Cohen's_h
Relative measure of dispersion expressed as the ratio of standard deviation to the mean
Standard score Information ratio Omega ratio Sampling (statistics) Variance function Everitt, Brian (1998). The Cambridge Dictionary of Statistics. Cambridge
Coefficient_of_variation
Distribution function associated with the empirical measure of a sample
an empirical distribution function (a.k.a. an empirical cumulative distribution function, eCDF) is the distribution function associated with the empirical
Empirical distribution function
Empirical_distribution_function
Approximation method in statistics
describes the variance in a prediction of the dependent variable as a function of the independent variable and the deviations from the fitted curve. When
Least_squares
Statistical method
all uniformly bounded functions from T {\displaystyle T} to R {\displaystyle \mathbb {R} } . When equipped with the uniform distance, ℓ ∞ ( T ) {\displaystyle
Bootstrapping_(statistics)
Statistics concept
statistical estimation problem it is linear, in the sense that the regression function E(y | x) is linear in the unknown parameters that are estimated from the
Polynomial_regression
}}{ds}}=I_{\lambda }-S_{\lambda }} where s is the distance measured along the path traveled by the beam. The minus sign on the left hand side shows that the intensity
Source_function
Function that measures dissimilarity between two probability distributions
information geometry, a divergence is a kind of statistical distance: a binary function which establishes the separation from one probability distribution
Divergence_(statistics)
Numerical measure of a statistical relationship between variables
numerical measure of some type of linear correlation, meaning a linear function between two variables. The variables may be two columns of a given data
Correlation_coefficient
Middle quantile of a data set or probability distribution
point or an empty set). Every convex function is a C function, but the reverse does not hold. If f is a C function, then f ( med [ X ] ) ≤ med [ f
Median
Data visualization
observed data point from the dataset that falls within this distance. Similarly, a distance of 1.5 times the IQR is measured out below the lower quartile
Box_plot
Statistical measure of how far values spread from their average
random variable X {\displaystyle X} is discrete with probability mass function x 1 ↦ p 1 , x 2 ↦ p 2 , … , x n ↦ p n {\displaystyle x_{1}\mapsto p_{1}
Variance
Fundamental theorem in probability theory and statistics
characteristic functions of a number of density functions becomes close to the characteristic function of the normal density as the number of density functions increases
Central_limit_theorem
Generalized function whose value is zero everywhere except at zero
Dirac delta function (or δ {\displaystyle {\boldsymbol {\delta }}} distribution), also known as the unit impulse, is a generalized function on the real
Dirac_delta_function
Method of determining minimum distance between two convex sets
other distance algorithms, it does not require that the geometry data be stored in any specific format, but instead relies solely on a support function to
Gilbert–Johnson–Keerthi distance algorithm
Gilbert–Johnson–Keerthi_distance_algorithm
Type of statistics
breakdown point and the influence function described below. The practical effect of problems seen in the influence function can be studied empirically by
Robust_statistics
Statistical measure of association
the function cramerV() from the package rcompanion calculates V using the chisq.test function from the stats package. In contrast to the function cramersV()
Cramér's_V
Class of statistical models
response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized
Generalized_linear_model
Type of statistical measure over subsets of a dataset
viewed as a low-pass finite impulse response filter. Because the boxcar function outlines its filter coefficients, it is called a boxcar filter. It is sometimes
Moving_average
Physics concept relating to automobiles
conditions, or when the driver's cognitive function is superior or deficient. To determine actual total stopping distance, one would typically empirically obtain
Braking_distance
Signs follow the general European conventions concerning the use of shape and colour to indicate function. Any text included on supplementary signs will
Road_signs_in_Norway
Replacing a number with a simpler value
524.811 up to 1098.892. For the examples below, sgn(x) refers to the sign function applied to the original number, x. One may round down (or take the floor
Rounding
How many standard deviations apart from the mean an observed datum is
and standard deviation of 1. Coefficient of variation Error function Mahalanobis distance Normalization (statistics) Omega ratio Standard normal deviate
Standard_score
Class of statistical estimators
M-estimators are a broad class of extremum estimators for which the objective function is a sample average. Both non-linear least squares and maximum likelihood
M-estimator
Sequence of data points over time
the autocorrelation function and the spectral density function (also cross-correlation functions and cross-spectral density functions) Scaled cross- and
Time_series
Graphical representation of the distribution of numerical data
and often for density estimation: estimating the probability density function of the underlying variable. The total area of a histogram used for probability
Histogram
Statistical methods to improve the quality of manufactured goods
includes three principal contributions to statistics: A specific loss function The philosophy of off-line quality control; and Innovations in the design
Taguchi_methods
Variable representing a random phenomenon
refers to neither randomness nor variability but instead is a mathematical function in which the domain is the set of possible outcomes in a sample space (e
Random_variable
Statistical sampling technique
only one in each axis-aligned hyperplane containing it. When sampling a function of N {\displaystyle N} variables, the range of each variable is divided
Latin_hypercube_sampling
Non-parametric statistic used to estimate the survival function
estimator, is a non-parametric statistic used to estimate the survival function from lifetime data. In medical research, it is often used to measure the
Kaplan–Meier_estimator
Nonparametric measure of rank correlation
relationship between two variables can be described using a monotonic function. The Spearman correlation between two variables is equal to the Pearson
Spearman's rank correlation coefficient
Spearman's_rank_correlation_coefficient
Mathematical approximation of a function
of a function is an infinite sum of terms that are expressed in terms of the function's derivatives at a single point. For most common functions, the
Taylor_series
Grouping a set of objects by similarity
algorithm and parameter settings (including parameters such as the distance function to use, a density threshold or the number of expected clusters) depend
Cluster_analysis
Function of the observed sample results
for instance using Fisher's combined probability test. The p-value is a function of the chosen test statistic T {\displaystyle T} and is therefore a random
P-value
Comparison of two distributions
distribution functions F and G, with associated quantile functions F−1 and G−1 (the inverse function of the CDF is the quantile function), the Q–Q plot
Q–Q_plot
Fourth standardized moment in statistics
type IV family restricted to symmetric densities. The probability density function (PDF) is given by f ( x ; a , m ) = Γ ( m ) a π Γ ( m − 1 / 2 ) [ 1 + (
Kurtosis
Measure of statistical dispersion
calculated by integrating the probability density function (which yields the cumulative distribution function—any other means of calculating the CDF will also
Interquartile_range
Statistical property
several individual quantities is known then the standard error of some function of the quantities can be easily calculated; when the probability distribution
Standard_error
SIGNED DISTANCE-FUNCTION
SIGNED DISTANCE-FUNCTION
SIGNED DISTANCE-FUNCTION
SIGNED DISTANCE-FUNCTION
SIGNED DISTANCE-FUNCTION
SIGNED DISTANCE-FUNCTION
SIGNED DISTANCE-FUNCTION
SIGNED DISTANCE-FUNCTION
SIGNED DISTANCE-FUNCTION