Ripe with possibilities offered by deep-learning techniques and useful in applications
related to remote sensing, computer vision, and robotics, 3D point cloud semantic …

Today 3D models and point clouds are very popular being currently used in several fields,
shared through the internet and even accessed on mobile phones. Despite their broad …

This paper introduces a novel, region-growing algorithm for the fast surface patch
segmentation of three-dimensional point clouds of urban environments. The proposed …

A fundamental problem in computer vision is that of inferring the intrinsic, 3D structure of the
world from flat, 2D images of that world. Traditional methods for recovering scene properties …

There is a growing need for tools automating the processing of as-built 3D laser scanned
data, and more particularly the comparison of this as-built data with planned works. This …

3D point cloud segmentation is the process of classifying point clouds into multiple
homogeneous regions, the points in the same region will have the same properties. The …

Palmprint processes a number of unique features for reliable personal recognition.
However, different types of palmprint images contain different dominant features. Instead …

Abstract 3D point cloud data from sensing technologies such as 3D laser scanning and
photogrammetry are able to capture the 3D surface geometries of target objects in an …

Many image segmentation techniques are available in the literature. Some of these
techniques use only the gray level histogram, some use spatial details while others use …

We present here a new algorithm for segmentation of intensity images which is robust, rapid,
and free of tuning parameters. The method, however, requires the input of a number of …