[talks] Yiming Liu will present his FPO on Wednesday, 12/9/2015 at 10am, 402 Computer Science.

Nicki Gotsis ngotsis at CS.Princeton.EDU
Wed Dec 2 10:51:35 EST 2015

Yiming Liu will present his FPO on Wednesday, 12/9/2015 at 10am, 402 Computer Science.

The members of his committee are Szymon Rusinkiewicz (advisor), readers: Aseem Agarwala (Google) and Adam Finkelstein; nonreaders: Jianxiong Xiao and Thomas Funkhouser.

A copy of his thesis, is available in Room 310.

Everyone is invited to attend his talk. The talk title and abstract follow below:

Title: Internet-Data-Driven Image Creation and Enhancement. 

Traditional systems for image creation and enhancement are completely reliant on
user input, either to generate content directly or to evaluate and tune algorithms.
The input must be generated by talented artists, and it is applicable only to the
image for which it was originally intended. This poses scalability challenges for such
traditional image generation and editing systems.
An alternative paradigm, which is being researched in a variety of contentgeneration
domains, is to exploit the large amount of data made available by users
over the Internet. This data may take many forms: images, image keywords, and
even judgments about image quality. Although the data is noisy and was not
originally intended for the task at hand, it nevertheless serves as a useful source
of “prior information.” These priors make it possible to build image creation and
enhancement systems that require only a small amount of user input, and do not
require the users to be professional artists or designers.
This thesis describes three such systems, including low-level image-processing (motion
deblurring), high-level editing (keyword-based image stylization), and image creation
(sketch-driven iconification). First, by learning based on a massive online user
study, we develop a metric for automatically predicting the perceptual quality of
images produced by motion deblurring algorithms, without access to the original images.
Second, by leveraging online image search engines, we investigate an approach
to photo filtering that only requires the user to provide one or more keywords. Third,
we develop a system that synthesize a variety of pictograms by remixing portions of
icons retrieved from a large online repository.

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