Acquisition of a Large Pose-Mosaic Dataset
Name
MIT-LCS-TM-568.pdf
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919.27 KB
Format
Adobe PDF
Checksum (MD5)
fab727f7e834ad2a1a87efbd7b06f918
Author(s)
Coorg, Satyan
Master, Neel
Teller, Seth
Date Issued
January 1998
Series/Report no.
MIT-LCS-TM-568
Abstract
We describe the generation of a large pose-mosaic dataset: a collection of several thousand digital images, grouped by spatial position into spherical mosaics, each annotated with estimates of the acquiring camera's 6 DOF pose (3 DOF position and 3 DOF orientation) in an absolute coordinate system. The pose-mosaic dataset was generated by acquiring images, grouped by spatial position into nodes (essentially, spherical mosaics). A prototype mechanical pan-tilt head was manually deployed to acquire the data. Manual surverying provided initial position estimates for each node. A back-projecting scheme provided initial rotational estimates. Relative rotations within each node, along with internal camera parameters, were refined automatically by an optimization-correlation scheme. Relative translations and rotations among nodes were refined according to point correspondences, generated automatically and by a human operator. The resulting pose-imagery is self-consistent under a variety of evaluation metrics. Pose-mosaics are useful "first-class" data objects, for example in automatic reconstruction of textured 3D CAD models which represent urban exteriors.
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