ORCID

http://orcid.org/0000-0002-8985-1084

Date of Award

Summer 2016

Author's School

School of Engineering & Applied Science

Author's Department

Computer Science & Engineering

Degree Name

Master of Science (MS)

Degree Type

Thesis

Abstract

Image datasets often live on a continuum: Images from an outdoor scene vary from day to night, across different weather conditions, and over the course of seasons. Faces age and exhibit different expressions. We consider the problem of taking individual images from these datasets and explicitly manipulating those images to change where they lie on the continuum. We focus on a version of this problem that requires as little input as possible, and we build off of previous work using CNN features to construct an intermediate image manifold on which to manipulate the images. We also investigate a novel way of reconstructing images from their CNN features using alpha compositions of the input images. These technique produce convincing semantic interpolations of images and timelapse video from a variety of sources.

Language

English (en)

Chair

Robert Pless

Committee Members

Tao Ju William Richard

Comments

Permanent URL: https://doi.org/10.7936/K7VH5M3V

Share

COinS