Visualization and Graphics ➤ Interaction ➤ Dept ICS ➤ Faculty of Science ➤ UU

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Readings

Reading material for this course consists of recommended books and articles, as follows.

Important note: Individual modules contain additional article pointers (see Slides).

Books

The course has no mandatory book. Students can take the course successfully without purchasing a specific book. However, this requires

  • a strong background in prerequisites (data representation, calculus, 3D graphics/imaging/modeling, statistics, linear algebra)
  • being present during all lectures (and making notes to complete the slides)

This being said, the following books contain all useful details concerning the presented theory, techniques, and implementation details. Note that each book focuses on different parts covered in the course:

Note: The books below are (or will be shortly) available through the book sale of Sticky

Handbook of Multimedia Information Retrieval

  • author: H. Eidenberger
  • publisher: Atpress
  • publication date: 2012
  • index information: ISBN 9783848222834

The book provides a good, broad, comprehensive overview of material discussed in the entire lecture.

Relevant material:

  • MR introduction (Chapters 2,3)
  • feature desceriptors (Chapters 5,7)
  • distances and matching (Chapter 8)
  • MR pipeline (Chapter 10)
  • local descriptors (Chapter 14)
  • evaluation (Chapter 20)
  • perception (Chapter 23)

Shape Analysis and Classification: Theory and Practice

  • author: L. Da Fontoura Costa, R. Marcondes Cesar Jr.
  • publisher: CRC Press
  • publication date: 2001 (subsequent editions are also fine)
  • index information: ISBN 9780849334931 (for 1st edition)

This book provides an excellent and detailed introduction to shape and image description, processing, and characterization.

Relevant material:

  • mathematical basic concepts (Chapter 2)
  • image processing (Sections 3.2, 3.3)
  • shape representation (Chapters 4,5)
  • shape features (Chapter 6)
  • shape classification (Sections 8.1, 8.3)
  • evaluation (Section 8.5)

Data Visualization - Principles and Practice (2nd edition)

  • author: A. C. Telea
  • publisher: CRC Press
  • publication date: 2014
  • index information: ISBN 9781466585263

This book provides a simpler, arguably more accessible and less math-heavy, coverage of MR data and shape representation and image processing than the previous book. It also discusses high-dimensional data from a practical perspective.

Relevant material:

  • basics of computer graphics (Chapter 2)
  • data representation (Chapter 3)
  • domain modeling techniques (Chapter 8; material on mesh refining/simplification only)
  • image processing (Chapter 9)
  • high-dimensional features, dimensionality reduction (Chapter 11).

A table of contents preview is available here.

Source code: The book comes with tens of algorithms implemented in plain C/C++ that cover computer graphics, 3D shape representation, sampled data representation, and more. All code samples are freely available in the online material coming with the book. Highly recommended as starting points for coding!

Articles

Visual Exploration of 3D Shape Databases via Feature Selection (X. Chen, G. Zeng, J. Kosinka, A. Telea. Proc. IVAPP, 2020)

The description of an end-to-end system for content-based retrieving of shapes from a 3D shape database. The practical assignment asks for implementing a very similar system (albeit with different features). Highly recommended to read before you start the assignment, but also during the execution of specific assignment steps!

A survey of content based 3D shape retrieval method (J. Tangelder, R. Veltkamp. Multimedia Tools and Applications 39(3), pp. 441-471, 2008)

An excellent survey of state-of-the-art methods for content-based 3D shape retrieval. Highly recommended!

Content-Based Image and Video Retrieval (R. Veltkamp, M. Tanase. In A Survey of Content-Based Image Retrieval Systems (Ch 5), pages 47-101. Kluwer, 2002)

An excellent survey of methods for content-based image/video retrieval.

3D Model Retrieval (D. Vranic, PhD thesis, Univ. Konstanz , 2003)

An in-depth discussion of 3D shape retrieval. Contains explanations, formulas, and implementation details for most feature descriptors discussed in this course.

Feature-based Similarity Search in 3D Object Databases (B. Bustos, D. Keim, D. Saupe, T. Schreck, D. Vranic. ACM Comput Surv 37(4), pp. 345-387 , 2005)

A condensed summary of the PhD thesis above. Good starting point for understanding similarity search.

Indexing techniques for multimedia data retrieval (J. Song. Encyclopedia of Database Systems (eds. L. Liu, M.T. Ozsu), Springer, 2017)

Short and easy-to-read overview of indexing techniques used for scaling up multimedia search.

3D Shape Matching with 3D Shape Contexts (M. Kortgen, G.-J. Park, M. Novotni, R. Klein. Proc. CESCG 2003)

Very readable paper describing how to compute and use shape context descriptors.

A descriptor for voxel shapes based on the skeleton cut space (C. Feng, A. Jalba, A. Telea. Proc. 3DOR 2016)

A simple example of content-based shape retrieval pipeline using skeletal descriptors. Useful to understand how an end-to-end CBSR pipeline is constructed.