Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Constraints on deformable models: recovering 3D shape and nongrid motion
Artificial Intelligence
Applications of dynamic monocular machine vision
Machine Vision and Applications
Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic extraction of deformable part models
International Journal of Computer Vision
LAPACK's user's guide
Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Introduction to Monte Carlo methods
Learning in graphical models
The Inventor Mentor: Programming Object-Oriented 3d Graphics with Open Inventor, Release 2
The Inventor Mentor: Programming Object-Oriented 3d Graphics with Open Inventor, Release 2
Tracking and Visualizing Turbulent 3D Features
IEEE Transactions on Visualization and Computer Graphics
The Application Visualization System: A Computational Environment for Scientific Visualization
IEEE Computer Graphics and Applications
Shape and Nonrigid Motion Estimation Through Physics-Based Synthesis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Global and local deformations of solid primitives
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
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Experimenting and building integrated, operational systems in computational vision poses both theoretical and practical challenges, involving methodologies from control theory, statistics, optimization, computer graphics, and interaction. Consequently, a control and communication structure is needed to model typical computer vision applications and a flexible architecture is necessary to combine the above mentioned methodologies in an effective implementation. In this paper, we propose a three-layer computer vision framework that offers: a) an application model able to cover a large class of vision applications; b) an architecture that maps this model to modular, flexible and extensible components by means of object-oriented and dataflow mechanisms; and c) a concrete software implementation of the above that allows construction of interactive vision applications. We illustrate how a variety of vision techniques and approaches can be modeled by the proposed framework and we present several complex, application oriented, experimental results.