Plane detection is a prerequisite to a wide variety of vision tasks. RANdom SAmple Consensus (RANSAC) algorithm is widely used for plane detection in point cloud data. Minimum description length (MDL) principle is used to deal with several competing hypothesis. This paper presents a new approach to the plane detection by integrating RANSAC and MDL. The method could avoid detecting wrong planes ...

To efficiently handle the continuously increasing raw point data-set sizes from high-resolution laser-range scanning devices or baseline stereo and multi-view 3D object reconstruction systems, powerful geometry processing solutions are required. We present a flexible and run-time configurable system for efficient out-of-core geometry processing of point cloud data that significantly extends and...

In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how di...

The goal of this work is to determine methods for detecting trails using statistics of LiDAR point cloud data, while avoiding reliance on a Digital Elevation Model (DEM). Creation of a DEM is a subjective process that requires assumptions be made about the density of the data points, the curvature of the ground, and other factors which can lead to very different results in the final DEM product...

A new method is required for change-point testing of precipitation data that is capable of applying valid precipitation models. First, stochastic precipation models are researched and classified. Typically, the occurrence of rain is modeled using a two-state, first-order Markov chain, and the intensity of rain is modeled using a two-parameter gamma distribution. Using the likelihood ratio test ...

Change-point problems arise when di/erent subsequences of a data series follow di/erent statistical distributions – commonly of the same functional form but having di/erent parameters. This paper develops an exact approach for 3nding maximum likelihood estimates of the change points and within-segment parameters when the functional form is within the general exponential family. The algorithm, a...

MOTIVATION In biomedicine, every molecular measurement is relative to a reference point, like a fixed aliquot of RNA extracted from a tissue, a defined number of blood cells, or a defined volume of biofluid. Reference points are often chosen for practical reasons. For example, we might want to assess the metabolome of a diseased organ but can only measure metabolites in blood or urine. In this ...

Point clouds, made available through laser range finders, stereo cameras, or time of flight cameras, are frequently used in robot navigation systems. However, no unsupervised machine perception algorithm exists to provide understanding of the data; e.g. that a particular blob of points looks roughly like, say, a car. In this paper, we take steps towards such an algorithm based on sparse coding....

Problems for parsing morphologically rich languages are, amongst others, caused by the higher variability in structure due to less rigid word order constraints and by the higher number of different lexical forms. Both properties can result in sparse data problems for statistical parsing. We present a simple approach for addressing these issues. Our approach makes use of self-training on instanc...