Object Representation in Computer Vision International NSF-ARPA Workshop, New York City, NY, USA, December 5 - 7, 1994. Proceedings
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...
| Other Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
1995, 1995
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| Edition: | 1st ed. 1995 |
| Series: | Lecture Notes in Computer Science
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- Report on the 1995 workshop on 3-D object representations in computer vision
- Object recognition: The search for representation
- Appearance-based 3D object recognition
- Using quasi-invariants for automatic model building and object recognition: An overview
- Object representation for recognition-by-alignment
- Distinctive representations for the recognition of curved surfaces using outlines and markings
- The epipolar parametrization
- Using two-dimensional models to interact with the three-dimensional world
- Representations for recognizing complex curved 3D objects
- On representation and invariant recognition of complex objects based on patches and parts
- Algebraic geometry and object representation in computer vision
- Discrete surface signal processing: The polygon as the surface element
- Spline representations in 3-D vision
- Triangles as a primary representation
- Body-centered representation and perception
- The challenge of generic object recognition
- A physics-based framework for segmentation, shape and motion estimation
- Modal represenations
- Time representation of deformations: Combining vibration modes and Fourier analysis
- Physics in a fantasy world vs robust statistical estimation
- Towards a robust physics-based object recognition system
- Toward non-parametric digital shape representation and recovery
- Spherical representations: From EGI to SAI
- From physics-based representation to functional modeling of highly complex objects