Dissertation/Thesis Abstract

Depth map enhancement for real-time 3D reconstruction
by Lee, Kitae, M.S., Illinois Institute of Technology, 2015, 49; 1603506
Abstract (Summary)

In this paper, we present a novel depth map enhancement for real-time 3D reconstruction by the Microsoft Kinect. The Kinect sensor is relatively affordable and capable of generating high-resolution color image and depth maps of the scene at real-time rates. However, owning the low- cost, there are several artifacts. Generated depth map contains lots of holes, which they are missing information around object boundaries and mis-alignment with color image. The objective of 3D reconstruction is to recreate a real scene, as accurate as possible within a virtual three-dimensional space using a computer. The algorithm of 3D-recosntrution is highly based on the quality of the depth map. This poor depth map could not be applied in potential real-time 3D reconstruction. We present novel multi-step upsampling-based our novel anisotropic diffusion algorithms with generated depth map and color image by Kinect. This method has better performance than existed bilateral filtering and original anisotropic filtering in terms of filling holes, sharpening the boundaries of objects and alignment between depth map and color image. We compare the performance of these filters. It is difficult to do a meaningful comparison of two algorithms with using output of Kinect sensor directly; as for each observation of the same scene, we will get different sensed value. In order to circumvent this problem and to achieve an accurate comparison process, we used dataset from Computer Vision Group at Munchen Technology Universty(TUM). This dataset and the scripts is related to quantitative error metrics are avail at http://vision.in.tum.de/data/datasets/rgbd-?dataset. We also contribute making our project parallel and GPU computing to satisfy real-time system condition.

Indexing (document details)
Advisor: Kim, Joohee
Commitee: Choi, Kyuwon, Wang, Jia
School: Illinois Institute of Technology
Department: Electrical and Computer Engineering
School Location: United States -- Illinois
Source: MAI 55/02M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Electrical engineering
Keywords: 3d reconstruction, Depth map, Image processing, Kinect
Publication Number: 1603506
ISBN: 978-1-339-22450-3
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