Computing the Aspect Graph for Line Drawing of Polyhedral Objects

Computing the Aspect Graph for Line Drawing of Polyhedral Objects
Author: University of California, Berkeley. Computer Science Division
Publisher:
Total Pages: 28
Release: 1988
Genre:
ISBN:

Koenderink and van Doorn introduced aspect graphs as a way of representing 3-D shape for object recognition. The set of viewpoints on the gaussian sphere is partitioned into regions such that in each region, the qualitative structure of the line drawing remains the same. The viewing data of an object is the partition of the gaussian sphere together with a representative line drawings for each region of the partition. In this paper we present an algorithm to compute the viewing data of polyhedral objects. In the course of presenting the algorithm, we provide a full catalog of the visual events that occur for this type of objects.

Object Recognition in Range Images Using CAD Databases

Object Recognition in Range Images Using CAD Databases
Author:
Publisher:
Total Pages: 14
Release: 1991
Genre:
ISBN:

An aspect graph plays an important role in three dimensional object recognition. Its represents the three-dimensional shape of an object by its two dimensional qualitative views as seen from various viewpoints. To create the aspect graph of an object, the viewpoint space is partitioned into regions, each of which corresponds to qualitatively similar projections of the object. Algorithms for creating aspect graphs of polyhedral objects have been developed. We developed an algorithm to compute the aspect graph of a curved object. Our approach partitions the viewpoint space by computing boundary viewpoints from the shape descriptions of the object given in a computer aided design database. These computations are formulated from the understanding of visual events and the locations of corresponding viewpoints. We also studied new visual events for piecewise smooth objects.

Cosmos

Cosmos
Author: Chitra Dorai
Publisher:
Total Pages: 512
Release: 1996
Genre: Computer vision
ISBN:

Shape, Contour and Grouping in Computer Vision

Shape, Contour and Grouping in Computer Vision
Author: David A. Forsyth
Publisher: Springer Science & Business Media
Total Pages: 340
Release: 1999-11-03
Genre: Computers
ISBN: 3540667229

Computer vision has been successful in several important applications recently. Vision techniques can now be used to build very good models of buildings from pictures quickly and easily, to overlay operation planning data on a neuros- geon’s view of a patient, and to recognise some of the gestures a user makes to a computer. Object recognition remains a very di cult problem, however. The key questions to understand in recognition seem to be: (1) how objects should be represented and (2) how to manage the line of reasoning that stretches from image data to object identity. An important part of the process of recognition { perhaps, almost all of it { involves assembling bits of image information into helpful groups. There is a wide variety of possible criteria by which these groups could be established { a set of edge points that has a symmetry could be one useful group; others might be a collection of pixels shaded in a particular way, or a set of pixels with coherent colour or texture. Discussing this process of grouping requires a detailed understanding of the relationship between what is seen in the image and what is actually out there in the world.

Object Representation in Computer Vision

Object Representation in Computer Vision
Author: Martial Hebert
Publisher: Springer Science & Business Media
Total Pages: 376
Release: 1995-10-18
Genre: Computers
ISBN: 9783540604778

This book documents the scientific outcome of the International NSF-ARPA Workshop on Object Representation in Computer Vision, held in New York City in December 1994 with invited participants chosen among the recognized experts in the field. The volume presents the complete set of papers in revised full-length versions. In addition, the first paper is a report on the workshop in which the panel discussions as well as the conclusions and recommendations reached by the workshop participants are summarized. Altogether the volume provides an excellent, in-depth view of the state of the art in this active area of research and applications.

Toward Category-Level Object Recognition

Toward Category-Level Object Recognition
Author: Jean Ponce
Publisher: Springer
Total Pages: 622
Release: 2007-01-25
Genre: Computers
ISBN: 3540687955

This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.

Representations and Techniques for 3D Object Recognition and Scene Interpretation

Representations and Techniques for 3D Object Recognition and Scene Interpretation
Author: Derek Santhanam
Publisher: Springer Nature
Total Pages: 147
Release: 2022-05-31
Genre: Computers
ISBN: 3031015576

One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions