Date Approved

5-4-2023

Embargo Period

5-16-2023

Document Type

Thesis

Degree Name

M.S. Electrical and Computer Engineering

Department

Electrical and Computer Engineering

College

Henry M. Rowan College of Engineering

Advisor

Ying (Gina) Tang, Ph.D.

Committee Member 1

Li, Jie, Ph.D.

Committee Member 2

Zhu Cheng, Ph.D.

Keywords

point cloud stitching, iterative closest point, K-nearest neighbor

Subject(s)

Three-dimensional modeling; Computer graphics

Disciplines

Electrical and Computer Engineering | Engineering

Abstract

The basic principle of stitching is joining or merging any two materials or objects. 3D point cloud stitching is basically stitching two 3D point cloud together. 3D point cloud stitching is an emerging topic and there are multiple ways to achieve it. There are various methods for stitching which all have changes throughout the time. The existing methods do have shortcomings and have ignored the multiangle stitching of a same model or an object. This shortfall leads to many deficiencies in the ability of a stitching algorithm to maintain accuracy over the period. In this work I have introduced a new approach for an iterative based approach for 3d multi-angle point cloud stitching using ICP (Iterative closest point algorithm) and KNN (K-nearest neighbor). The design follows an incremental approach to achieve the results. This is a novel approach of stitching multiple 3D point clouds taken from multiple angles of a single bust. The framework is evaluated based on the stitching results provided by the algorithm capability of stitching multiple point cloud into a solid model.

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