University of Konstanz
Graduiertenkolleg / PhD Program
Computer and Information Science

Ioan Cleju

Doctoral Student in the PhD program since 01.01.2005.
May 2, 2006 - July 31, 2006: on leave at McMaster University, Hamilton, Ontario, Canada, with Prof. Dr. Xiaolin Wu. Octobre, 2008 - Graduation

advisors

1. Prof. Dr. Dietmar Saupe
2. Prof. Dr. Ulrik Brandes

organisational data

Room: Z 713
Tel.: +49 (0)7531 / 88-2200
E-mail: firstname.lastname "at" uni-konstanz.de
Other Resources: http://www.inf.uni-konstanz.de/~cleju/
picture

project description

Perceptual Distances and Texture Registration for 3D Models

Quantifying the perceived dissimilarity between 3D models and their simplified copies is necessary for assessing the quality of simplification and compression algorithms, and for Level-Of-Detail (LOD) management. This thesis examines several strategies used for the evaluation of objective distances with respect to user studies. We show that ordinal analysis on the LOD sequences does not provide enough data to differentiate between several objective distances. Popular evaluation strategies, such as based on ratings, provide however ordinal data. We propose a new experimental setup that allows parametric evaluation of objective distances with respect to the user study. The case study included six objective distance measures and we found that all image-based distances were better than those geometric-based.

A second topic covered in this thesis is texture registration for 3D models. The common 3D acquisition pipeline considers geometry acquisition (by 3D scanning) and texture acquisition (by photographing) as two independent steps. The texture registration solves the 2D-3D mapping problem by recovering the parameters of the photo cameras. Commonly, the patches of the model are visible in several images. We propose to use this additional information to improve the registration algorithm by adding corresponding objective functions. We define objective functions based on mutual information between each image and the surface model and between each pairs of images that sample a common patch of the surface. The mutual information has several advantages over other registration criteria, including that it is robust and does not need preprocessing and feature extraction. In various experiments we showed that the extended optimization approach is more robust with respect to the initialization and leads to increased accuracy of registration.

publications

The following list of publications covers only those, which are or were published during participation at the Graduiertenkolleg / PhD program.

Articles in Journals

2010

Conference Papers

2010200720062005
2010
2007
2006
2005

Phd Theses

2008

awards

curriculum vitae

2003 - 2004 Studies of Computer Science at University of Joensuu, Finland
Degree: M.Sc. 
2001 - 2002 Working at Isratech Romania as asic designer.
1998 - 2003 Studies of Computer Engineering at Technical University Gh. Asachi, Iasi, Romania
Degree: Diploma Engineer.