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Fiducial Planning for Error-Bounded Pose Estimation of a Panoramic Camera in Large Environments
 

Summary: Fiducial Planning for Error-Bounded Pose Estimation of a
Panoramic Camera in Large Environments
Daniel G. Aliaga Ingrid Carlbom
{aliaga|carlbom}@bell-labs.com
Lucent Technologies Bell Labs
1. INTRODUCTION
Panoramic image sensors are becoming increasingly popular because they capture large portions of the visual field
in a single image. These cameras are particularly effective for capturing and navigating through large, complex 3D
environments. Existing vision-based camera pose algorithms are derived for standard field-of-view cameras, but
few algorithms have been proposed to take advantage of the larger field-of-view of panoramic cameras.
Furthermore, while existing camera pose estimation algorithms work well in small spaces, they do not scale well to
large, complex 3D environments consisting of a number of interconnected spaces.
Accurate and robust estimation of the position and orientation of image sensors has been a recurring problem in
computer vision, computer graphics, and robot navigation. Stereo reconstruction methods use camera pose for
extracting depth information to reconstruct a 3D environment [12, 16]. Image-based rendering techniques [1, 3, 15,
19, 20, 28] require camera position and orientation to recreate novel views of an environment from a large number
of images. Augmented reality systems [5] use camera pose information to align virtual objects with real objects, and
robot navigation and localization methods [7, 8, 10, 30] must be able to obtain the robot's current location in order
to maneuver through a (captured) space.
We can divide existing vision-based camera pose approaches into passive methods and active methods. Passive

  

Source: Aliaga, Daniel G. - Department of Computer Sciences, Purdue University
Singh, Jaswinder Pal - Department of Computer Science, Princeton University

 

Collections: Computer Technologies and Information Sciences