Real-time Incremental Surface Reconstruction from Streaming Point Cloud

MPhil Thesis Defence


Title: "Real-time Incremental Surface Reconstruction from Streaming Point 
Cloud"

By

Mr. Nuoyuan YAN


Abstract

Surface reconstruction, also known as mesh reconstruction, is a critical 
step in 3D reconstruction pipeline that generates 3D models from a series 
of images of a specific objects. The input of the surface reconstruction 
is a sparse 3D point cloud obtained from Structure-from-Motion (SfM) and 
the output is a 3D model represented by a mesh. In general, this process 
is implemented off-line because it requires a cost calculation of 
optimizing labelling energy and cannot insert or remove points 
dynamically. In this thesis, a new reconstruction method is implemented 
which can incrementally extract surface from tetrahedra after the 
triangulation from streaming point cloud. A novel energy function is 
harnessed in order to reduce the time complexity and without losing the 
accuracy comparing to state-of-the-art method. By utilizing this energy 
function and dynamic version of graph cut algorithm, the reconstruction 
process can be achieved in real-time and dynamic manner. With this 
implementation, 3D reconstruction can be applied in the real-time 
applications such as Simultaneous Localization and Mapping (SLAM).


Date:			Friday, 17 January 2020

Time:			4:00pm - 6:00pm

Venue:			Room 5501
 			Lifts 25/26

Committee Members:	Prof. Long Quan (Supervisor)
 			Prof. Chiew-Lan Tai (Chairperson)
 			Dr. Pedro Sander


**** ALL are Welcome ****