With the ever-increasing popularity of unmanned aerial vehicles and other platforms providing dense point clouds, filters for identification ground points in such clouds are needed. Many have been proposed widely used, usually based on determination an original surface approximation subsequent within a predefined distance from surface. We presented new filter, multidirectional shift rasterizati...

In many applications, denoising is necessary since point-sampled models obtained by laser scanners with insufficient precision. An algorithm for point-sampled surface is presented, which combines fuzzy c-means clustering with mean shift filtering algorithm. By using fuzzy c-means clustering, the largescale noise is deleted and a part of small-scale noise also is smooth. The cluster centers are ...

3D depth sensors such as LIDARs and RGB-D cameras have become a popular choice for indoor localization and mapping. However, due to the lack of direct frame-to-frame correspondences, the tracking traditionally relies on the iterative closest point technique which does not scale well with the number of points. In this paper, we build on top of more recent and efficient density distribution align...

We study the problem of estimating the ridges of a density function. Ridge estimation is an extension of mode finding and is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data. We show that, under mild regularity conditions, the ridges of the kernel density estimator consistently estimate the ridges of the true density. When the...

 ABSTRACT Background: Acute appendicitis is the most common cause of acute surgical abdomen. Inspite of the introduction of ultrasonography, computed tomography scanning and laparoscopy in the years 1987-1997 the difficulty in accurate diagnosis of acute appendicitis has remained the same. Our way of reaching a decision for operating in a patient suspected of having acute appendicitis (which wi...

This paper deals with the application for contentbased image retrieval to extract color feature from natural images stored in the image database by segmenting the image through clustering. We employ a class of nonparametric techniques in which the data points are regarded as samples from an unknown probability density. Explicit computation of the density is avoided by using the mean shift proce...