Segmentation and Recovery of Superquadrics

1. Auflage. Softcover version of original hardcover Auflage 2000
ISBN: 978-90-481-5574-3
Verlag: Springer Netherlands

Buch, Englisch, Band 20, 266 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 446 g

Reihe: Computational Imaging and Vision

A representation of objects by their parts is the dominant strategy for representing complex 3D objects in many disciplines. In computer vision and robotics, superquadrics are among the most widespread part models. Superquadrics are a family of parametric models that cover a wide variety of smoothly changing 3D symmetric shapes, which are controlled with a small number of parameters and which can be augmented with the addition of global and local deformations. The book covers, in depth, the geometric properties of superquadrics. The main contribution of the book is an original approach to the recovery and segmentation of superquadrics from range images. Several applications of superquadrics in computer vision and robotics are thoroughly discussed and, in particular, the use of superquadrics for range image registration is demonstrated.
The book is intended for readers of all levels who are familiar with and interested in computer vision issues.

Zielgruppe

Research

Autoren/Hrsg.

Jaklic, Ales

Solina, F.

Leonardis, Ales

Fachgebiete

• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik

Inhaltsverzeichnis

1. Introduction.- 2. Superquadrics and Their Geometric Properties.- 3. Extensions of Superquadrics.- 4. Recovery of Individual Superquadrics.- 5. Segmentation with Superquadrics.- 6. Experimental Results.- 7. Applications of Superquadrics.- 8. Conclusions.- Appendices.- B— Superquadric Recovery Code.- C— Range Image Acquisition.- D— Minimum Description Length and Maximum A Posteriori Probability.- E— Object-Oriented Framework for Segmentation (Segmentor).- References.- Author Index.- Topic Index.