Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision
(CS 528)

A General Linear Camera Model with Applications

Leonard McMillan, University of North Carolina at Chapel Hill
October 25, 2004, 4:15PM
TCSeq 200
http://graphics.stanford.edu/ba-colloquium/

Abstract

I will present a General Linear Camera (GLC) model that unifies many previous camera models into a single representation. The GLC model describes all perspective (pinhole), orthographic, and many multiperspective (including pushbroom and two-slit) cameras, as well as epipolar plane images. It also includes three new, previously unexplored, multiperspective linear cameras. The GLC model is both general and linear in the sense that, given any vector space where rays are represented as points, it describes all 2D affine subspaces (planes) formed by the affine combination of 3 rays. The incident radiance seen along the rays of these 2D affine subspaces are a precise definition of a projected image of a 3D scene. The GLC model also provides an intuitive physical interpretation, which can be used to characterize real imaging systems. Since the GLC model provides a complete description of all 2D affine subspaces, it can be used as a tool for first-order differential analysis of arbitrary (higher-order) multiperspective imaging systems. I will demonstrate applications of the GLC camera model for generating multiperspective panoramas, neocubist-style renderings, and faux animations from still-life scenes. Finally, I will speculate on how GLCs can be used in compute vision applications and in the analysis of catadioptric imaging systems.

About the Speaker

Leonard McMillan is an Associate Professor of Computer Science at the University of North Carolina in Chapel Hill. Leonard is a pioneer in the field of image-based rendering. Image-based rendering is an approach to computer graphics where scenes are rendered directly from collections of reference images rather than from geometric models. Leonard also works in a wide-range of related areas including computer vision, multimedia, image processing, and computer architecture.

Contact: bac-coordinators@cs.stanford.edu

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