Point cloud completion is a generation and estimation issue derived from the partial point clouds, which plays vital role in applications of 3D computer vision. The progress deep learning (DL) has impressively improved capability robustness completion. However, quality completed clouds still needed to be further enhanced meet practical utilization. Therefore, this work aims conduct comprehensiv...

Finding the k nearest neighbours of each point in a point cloud forms an integral part of many point-cloud processing tasks. One common approach is to build a kd-tree over the points and then iteratively query the k nearest neighbors of each point. We introduce a simple modification to these queries to exploit the coherence between successive points; no changes are required to the kd-tree data ...

This paper presents an automated and effective framework for classifying airborne laser scanning (ALS) point clouds. The framework is composed of four stages: (i) step-wise point cloud segmentation, (ii) feature extraction, (iii) Random Forests (RF) based feature selection and classification, and (iv) post-processing. First, a step-wise point cloud segmentation method is proposed to extract thr...

Point cloud simplification has become a vital step in any point-based surface processing pipeline. This paper describes a fast and effective algorithm for point cloud simplification with feature preservation. First, feature points are extracted by thresholding curvatures; Second, for non-feature points, they are covered by distinct balls, the points in each ball are substituted by an optimized ...

in this study, porous scaffolds from poly(d,l-lactic acid) have been prepared via liquid- liquid phase separation method in ternary system of polymer-1,4-dioxane-water. polymer dissolved in dioxane in 1.5, 2.5 and 5 % wt/v and the solvent/non-solvent ratios were 13/87, 15/85 and 17/83. cloud point curves prepared by visual turbidometry. in order to obtain porous scaffolds with inter-connected p...

Combining active and passive imaging sensors enables creating a more detailed 3D model of the real world. Then, these 3D data can be used for various applications, such as city mapping, indoor navigation, autonomous vehicles, etc. Typically, LiDAR and camera as imaging sensors are installed on these systems. Both of these sensors have advantages and drawbacks. Thus, LiDAR sensor directly provid...

Airborne Light Detection and Ranging (LiDAR) has the ability of acquiring huge and highly accurate point cloud. Therefore, the processing of huge point clouds has become an important research topic and has drawn increasing attention in the fields of remote sensing. In this paper, an automatic three-dimensional (3D) model retrieval system is introduced to retrieve building models using point clo...