Date of Award

Summer 8-15-2016

Author's Department

Computer Science & Engineering

Degree Name

Doctor of Philosophy (PhD)

Degree Type

Dissertation

Abstract

This dissertation explores an alternative to traditional fiducial markers where geometric

information is inferred from the observed position of 3D points seen in an image. We offer an alternative approach which enables geometric inference based on the relative orientation

of markers in an image. We present markers fabricated from microlenses whose appearance

changes depending on the marker's orientation relative to the camera. First, we show how

to manufacture and calibrate chromo-coding lenticular arrays to create a known relationship

between the observed hue and orientation of the array. Second, we use 2 small chromo-coding lenticular arrays to estimate the pose of an object. Third, we use 3 large chromo-coding lenticular arrays to calibrate a camera with a single image. Finally, we create another type of fiducial marker from lenslet arrays that encode orientation with discrete black and white appearances. Collectively, these approaches oer new opportunities for pose estimation and camera calibration that are relevant for robotics, virtual reality, and augmented reality.

Language

English (en)

Chair

Robert Pless

Committee Members

Bryan Clair, Yasutaka Furukawa, Viktor Gruev, Tao Ju, Joseph O'Sullivan

Comments

Permanent URL: https://doi.org/10.7936/K74F1P4D

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