Indoor Scene Localization to Fight Sex Trafficking in Hotels

<p>Images are key to fighting sex trafficking. They are: (a) used to advertise for sex services,(b) shared among criminal networks, and (c) connect a person in an image to the place where the image was taken. This work explores the ability to link images to indoor places in order to support the investigation and prosecution of sex trafficking. We propose and develop a framework that includes a database of open-source information available on the Internet, a crowd-sourcing approach to gathering additional images, and explore a variety of matching approaches based both on hand-tuned features such as SIFT and learned features using state of the art deep learning approaches. We concentrate on spatio-temporal indexing of hotel rooms, and to date have an index of more than 1.5 million geo-coded images. Our smart-phone app collects contextual information and metadata alongside images.</p>

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science & Engineering

Year dc:date.available

2016

Author dc:creator

• Stylianou, Abigail

Contributors dc:contributor

• Robert Pless
• Yasutaka Furukawa Sanmay Das

• computer vision
• sex trafficking
• scene recognition
• localization
• image matching
• Artificial Intelligence and Robotics
• Engineering
• Forensic Science and Technology
• Physical Sciences and Mathematics

Statement dc:rights

• I have not registered my thesis with the U.S. Copyright Office, and do not intend to.

Language dc:language

English (en)

Identifier

https://openscholarship.wustl.edu/eng_etds/198

OAI identifier oai:identifier

oai:openscholarship.wustl.edu:eng_etds-1198