Author ORCID Identifier
Date Available
12-7-2018
Year of Publication
2018
Document Type
Doctoral Dissertation
Degree Name
Doctor of Philosophy (PhD)
College
Engineering
Department/School/Program
Computer Science
Advisor
Dr. Nathan Jacobs
Abstract
Human appearance is highly variable and depends on individual preferences, such as fashion, facial expression, and makeup. These preferences depend on many factors including a person's sense of style, what they are doing, and the weather. These factors, in turn, are dependent upon geographic location and time. In our work, we build computational models to learn the relationship between human appearance, geographic location, and time. The primary contributions are a framework for collecting and processing geotagged imagery of people, a large dataset collected by our framework, and several generative and discriminative models that use our dataset to learn the relationship between human appearance, location, and time. Additionally, we build interactive maps that allow for inspection and demonstration of what our models have learned.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2018.469
Recommended Citation
Bessinger, Zachary, "Modeling and Mapping Location-Dependent Human Appearance" (2018). Theses and Dissertations--Computer Science. 75.
https://uknowledge.uky.edu/cs_etds/75
Included in
Applied Statistics Commons, Artificial Intelligence and Robotics Commons, Geographic Information Sciences Commons, Human Geography Commons
