In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

Nikolaos Sarafianos

will defend his dissertation

Person Search Using Identity Attributes

Abstract

The goal of this dissertation is to develop and evaluate algorithms and a prototype system to retrieve frames depicting humans with specific identity attributes obtained from a textual description. Solving this problem requires addressing three separate subproblems, namely (i) defining the ontology of the identity and the identity-related attributes, (ii) developing and evaluating algorithms for extracting identity attributes from images, and (iii) developing and evaluating an algorithm for attribute-based person search in databases of image frames. This dissertation presents a list of methods on visual attribute classification and person search that significantly improves the accuracy over previous work. The methods presented tackle key limitations of previous work such as the class imbalance of visual attributes, or the challenge of learning discriminative representations from the textual input. By learning to retrieve the most relevant images of individuals based on textual descriptions, such techniques can have a broader impact in cases of missing children or in surveillance applications. The works introduced in this dissertation, capable of successfully identifying which images contain humans with such characteristics, could reduce dramatically the effort and the time required to identify such information.

Date: Friday, April 12, 2019
Time: 10:30 AM - 12:00 PM
Place: HBS 317
Advisors: Dr. Ioannis A. Kakadiaris

Faculty, students, and the general public are invited.