CSC 6991  Digital Metaverse (VR/AR/MR/AI) Foundation: 3D Graphical and Geometric Modeling (Winter 2024)



Important Notices:



Course Information:

Course Ref. No.: 24975

Term: Winter 2024

Time: Tue & Thu 2:30 PM - 3:45 PM

Location: 3115 State Hall


Instructor Contact Information:

Name: Zichun Zhong

Phone Number: 313-577-9530

Office Location: 5057 Woodward Ave, Suite 14109.2, Detroit, Michigan, 48202

Office Hours: Tue & Thu 1:30 PM - 2:30 PM (by appointment)

Email Address: zichunzhong@wayne.edu

TA: TBD


Course Description and Goals: 

The main focus of the course is to introduce theoretic and computational background of modeling in 3D computer graphics, geometric processing, and visualization, specifically, how to represent, model, and analyze 3D models and scenes. For instance, "how can we build a high-quality model from acquired large-scale 3D dataset in a complex scenario (i.e., scanned data, medical images, unorganized sets of polygons, voxels, etc.)?" and "how can we use the 3D model for reconstruction, simulation, and animation?" The goal of this course is after learning basic computer graphics programming, knowledge, and geometry concepts, students will get to the latest and most popular 3D data representation schemes and techniques; and know how to effectively use them in different graphics, computer-aided design, simulation, or animation applications. The following topics will be covered:

  • Basics in Computer Graphics and Geometric Modeling 
  • Introduction to OpenGL Programming 
  • Representation of 3D Objects 
  • 3D Reconstruction Issues 
  • 3D Surface Mesh Generation 
  • 3D Volume Mesh Generation 
  • Reconstruction of 3D Volume Image from 2D Projections 
  • Reconstruction of 3D Mesh from Point Clouds 
  • Reconstruction of 3D Meshes from Images, such as CT/MRI Medical Images 
  • Simplification of 3D Meshes 
  • Subdivision 3D Surfaces 
  • Deep Learning in 3D Geometry and VR/AR 



Required Textbook:

  • Mario Botsch, Leif Kobbelt, Mark Pauly, Pierre Alliez, Bruno Lévy, Polygon Mesh Processing, CRC Press, 2010, ISBN: 9781568814261. The book source code, data, and slides are included.
  • Some course topics and materials are selected from top journals and conferences in computer graphics and visualization fields, such as ACM TOG, IEEE TVCG, CAD, CAGD, SIGGRAPH, IEEE Visualization, SGP, SPM, GMP, MICCAI, CVPR, ICCV, ECCV, etc.

Recommended Reference Book:





Useful Graphics Books: 

  • OpenGL Programming Guide: The Official Guide to Learning OpenGL, Versions 4.3 (8th Edition), Addison Wesley, 2013. ISBN-13: 978-0321773036. A free online version: http://www.glprogramming.com/red/
  • Interactive Computer Graphics: A Top-Down Approach with WebGL (7th Edition), Pearson, ISBN-13: 978-0133574845.

OpenGL Programming Guide and Environments:

  • Running OpenGL/GLUT with Visual Studio 2005/2008/2010

  • Lecture Notes: (All slides and reference materials are posted on Canvas at WSU)

    Syllabus (Check it on Canvas)

    Blue color is done

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    Date

    Subject

    01/09/2024

    Introduction to 3D Graphical and Geometric Modeling and Applications

    01/11/2024

    Introduction to Computer Graphics and OpenGL

    01/16/2024

    Representation of 3D Shapes

    01/18/2024

    Mesh Data Structure

    01/23/2024

    Mesh Data Structure

    01/25/2024

    3D Surface Mesh Generation

    01/30/2024

    3D Surface Mesh Generation

    02/01/2024

    3D Surface Mesh Generation

    02/06/2024

    -

    02/08/2024

    Proposal Discussion

    02/13/2024

    3D Surface Mesh Generation

    02/15/2024

    3D Volume Mesh Generation

    02/20/2024

    3D Volume Mesh Generation

    02/22/2024

    Reconstruction of 3D Volume Images from 2D Projections

    02/27/2024

    Reconstruction of 3D Volume Images from 2D Projections

    02/29/2024

    Reconstruction of 3D Meshes from Point Clouds

    03/05/2024

    Reconstruction of 3D Meshes from Point Clouds

    03/07/2024

    Mid-Term Presentation

    03/12/2024

    Spring Break - No Class

    03/14/2024

    Spring Break - No Class

    03/19/2024

    Reconstruction of 3D Meshes from Point Clouds

    03/21/2024

    Reconstruction of 3D Meshes from 2D/3D Images

    03/26/2024

    Reconstruction of 3D Meshes from 2D/3D Images

    03/28/2024

    Simplification of 3D Meshes

    04/02/2024

    Simplification of 3D Meshes

    04/04/2024

    Simplification of 3D Meshes

    04/09/2024

    Subdivision 3D Surfaces

    04/11/2024

    3D Deep Learning on Geometry and Shapes

    04/16/2024

    3D Deep Learning on Geometry and Shapes

    04/18/2024

    Final Presentation and Demo




    Grading: 

    (1)   Proposal: 10% (Due date: 02/08/2024)

    -          Study a set of relevant papers (3-5 papers)

    -          Give a class presentation and submit your own 1-2 page course project proposal (for a specific topic/algorithm/method taught by this course)

    (2)   Mid-term report and presentation: 10% (Due date: 03/07/2024)

    -          Submit your 1-2 page mid-term report and implement basic functionalities of your proposed project before the mid-term check point

    -          Give a class presentation

    (3)   Final presentation and demo: 20% (Due date: 04/18/2024)

          -     Give a class presentation and final project demonstration

          (4) Project submission: 60% (Due date: 04/18/2024)

          -     Submit your project code and 1-2 page final project report




    Prerequisites: This is a graduate-level course. But undergraduate students would still be able to take this course. Some basic background in linear algebra and programming (CSC 2000 or equivalent) is assumed. Knowledge about computer graphics (CSC 5870) and geometry will be helpful.



    Course & Instructor Policies:

    (1) Copying source code from another student in this class or obtaining a solution from some other source will lead to an automatic failure for this course and to a disciplinary action. In this case, you may be given a score of 0 for the assignment or project in question (and the other party will get a failure).

    (2) No late submission for assignment will be accepted.

    (3) Grades will be posted on the Canvas.

    (4) If there is any special case, please inform the instructor in advance.