List of datasets in computer vision and image processing
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Random sample consensus (RANSAC) is an iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers, when outliers are to be accorded no influence on the values of the estimates. Therefore, it also can be interpreted as an outlier detection method.[1] It is a non-deterministic algorithm in the sense that it produces a reasonable result only with a certain probability, with this probability increasing as more iterations are allowed. The algorithm was first published by Fischler and Bolles at SRI International in 1981. They used RANSAC to solve the Location Determination Problem (LDP), where the goal is to determine the points in the space that project onto an image into a set of landmarks with known locations.
RANSAC uses repeated random sub-sampling.[2] A basic assumption is that the data consists of "inliers", i.e., data whose distribution can be explained by some set of model parameters, though may be subject to noise, and "outliers" which are data that do not fit the model. The outliers can come, for example, from extreme values of the noise or from erroneous measurements or incorrect hypotheses about the interpretation of data. RANSAC also assumes that, given a (usually small) set of inliers, there exists a procedure which can estimate the parameters of a model that optimally explains or fits this data.
^Data Fitting and Uncertainty, T. Strutz, Springer Vieweg (2nd edition, 2016)
^Cantzler, H. "Random Sample Consensus (RANSAC)". Institute for Perception, Action and Behaviour, Division of Informatics, University of Edinburgh. Archived from the original on 2023-02-04.
and 21 Related for: Random sample consensus information
Randomsampleconsensus (RANSAC) is an iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers...
deviation, or the Latin letter s, for the sample standard deviation. The standard deviation of a random variable, sample, statistical population, data set, or...
Retrieved on 24 November 2014. M. A. Fischler, R. C. Bolles. RandomSampleConsensus: A Paradigm for Model Fitting with Applications to Image Analysis...
matched. This is why the matches should also be filtered. RANSAC (randomsampleconsensus) is the algorithm that is usually used to remove the outlier correspondences...
used is known as RANSAC. The name RANSAC is an abbreviation for "RANdomSAmpleConsensus". It is an iterative method for robust parameter estimation to...
algorithms that rely on repeated randomsampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be...
G(K) in the Gordon–Newell theorem RANSAC (an abbreviation for "RANdomSAmpleConsensus"): an iterative method to estimate parameters of a mathematical...
representing all sample pairs always clustering together or not together over all resampling iterations. The relative stability of the consensus matrices can...
observed data are in effect a randomsample of all the participants assigned a particular intervention. With MCAR, the random assignment of treatments is...
logo is created from a collection of aligned sequences and depicts the consensus sequence and diversity of the sequences. Sequence logos are frequently...
statistics Random regular graph RandomsampleRandomsamplingRandom sequence Random variable Random variate Random walk Random walk hypothesis Randomization Randomized...
observable sample mean is a residual. Note that, because of the definition of the sample mean, the sum of the residuals within a randomsample is necessarily...
to outliers but recent approaches deal with outliers by using randomsampleconsensus (RANSAC) and enhanced Dirichlet process mixture models. Other approaches...
PMID 25544679. Martin A. Fischler & Robert C. Bolles (June 1981). "RandomSampleConsensus: A Paradigm for Model Fitting with Applications to Image Analysis...
the resulting estimate. To illustrate its effect, we take a simulated randomsample from the standard normal distribution (plotted at the blue spikes in...
using this consensus-estimate allows us to attain at least 1/3.39 of the optimal profit, even in worst-case scenarios. Random-sampling mechanism - an...
discontinuous sinusoidal waveforms. Machine learning techniques such as Randomsampleconsensus (RANSAC) and Density-based spatial clustering of applications with...