International Journal of Computer Vision

, Volume 36, Issue 2, pp 101–130

Systems and Experiment Paper: Construction of Panoramic Image Mosaics with Global and Local Alignment

  • Heung-Yeung Shum
  • Richard Szeliski

DOI: 10.1023/A:1008195814169

Cite this article as:
Shum, HY. & Szeliski, R. International Journal of Computer Vision (2000) 36: 101. doi:10.1023/A:1008195814169


This paper presents a complete system for constructing panoramic image mosaics from sequences of images. Our mosaic representation associates a transformation matrix with each input image, rather than explicitly projecting all of the images onto a common surface (e.g., a cylinder). In particular, to construct a full view panorama, we introduce a rotational mosaic representation that associates a rotation matrix (and optionally a focal length) with each input image. A patch-based alignment algorithm is developed to quickly align two images given motion models. Techniques for estimating and refining camera focal lengths are also presented.

In order to reduce accumulated registration errors, we apply global alignment (block adjustment) to the whole sequence of images, which results in an optimally registered image mosaic. To compensate for small amounts of motion parallax introduced by translations of the camera and other unmodeled distortions, we use a local alignment (deghosting) technique which warps each image based on the results of pairwise local image registrations. By combining both global and local alignment, we significantly improve the quality of our image mosaics, thereby enabling the creation of full view panoramic mosaics with hand-held cameras.

We also present an inverse texture mapping algorithm for efficiently extracting environment maps from our panoramic image mosaics. By mapping the mosaic onto an arbitrary texture-mapped polyhedron surrounding the origin, we can explore the virtual environment using standard 3D graphics viewers and hardware without requiring special-purpose players.

image mosaicsvirtual environment modelingpanoramasparametric motion estimationglobal alignmentlocal alignment

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Heung-Yeung Shum
    • 1
  • Richard Szeliski
    • 1
  1. 1.Microsoft ResearchRedmondUSA