Summary: ACM Transactions on Graphics, to appear, 2009.
A Framework for Modeling 3D Scenes using Pose-free Equations
DANIEL G. ALIAGA, JI ZHANG, MIREILLE BOUTIN
Many applications in computer graphics require detailed 3D digital models of real-world environments. The automatic and semi-automatic
modeling of such spaces presents several fundamental challenges. In this work, we present an easy and robust camera-based acquisition approach
for the modeling of 3D scenes which is a significant departure from current methods. Our approach uses a novel pose-free formulation for 3D
reconstruction. Unlike self-calibration, omitting pose parameters from the acquisition process implies no external calibration data must be
computed or provided. This serves to significantly simplify acquisition, to fundamentally improve the robustness and accuracy of the geometric
reconstruction given noise in the measurements or error in the initial estimates, and to allow using uncalibrated active correspondence methods to
obtain robust data. Aside from freely taking pictures and moving an uncalibrated digital projector, scene acquisition and scene point
reconstruction is automatic and requires pictures from only a few viewpoints. We demonstrate how the combination of these benefits has enabled
us to acquire several large and detailed models ranging from 0.28 to 2.5 million texture-mapped triangles.
Categories and Subject Descriptors: I.3 [Computer Graphics], I.3.3 [Picture/Image Generation], I.3.7 [Three-dimensional Graphics and
Realism], I.4.1 [Digitization and Image Capture].
General Terms: modeling, acquisition, image-based
Additional Key Words and Phrases: computer graphics, modeling, acquisition, image-based rendering, pose-free.
The acquisition and modeling of complex real-world