Date of Award
2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computer Science
Committee Chair
Tathagata Mukherjee
Committee Member
Sundar Christopher
Committee Member
Huaming Zhang
Committee Member
Vineetha Menon
Committee Member
Chaity Banerjee
Research Advisor
Tathagata Mukherjee
Subject(s)
Image processing--Digital techniques, Pattern recognition systems, Computer vision, Artificial intelligence
Abstract
In this dissertation we study frameworks for image matching for three distinct application scenarios: the first relates to positioning in GPS agnostic environments, the second relates to matching and retrieving similar images in an indoor environment sourced from multiple uncalibrated cameras and the third relates to matching and retrieving satellite images across multiple uncalibrated satellite cameras. We propose three different frameworks the first one based on the idea of transformers, the second one based on the idea of autoencoders and the third one based on the idea of Siamese networks. We report extensive experiments with novel datasets for each of these scenarios. For the first we use a novel high altitude aerial image dataset obtained from Leon county GIS in Florida and a publicly available dataset curated from Google Earth, for the second we curate our own dataset at UAH and use it for our experiments. Finally, for the third we use dataset from Maxar and Planet obtained at the courtesy of NASA.
Recommended Citation
Phatate, Praveen Vijayakumar, "Frameworks for multi-source image search using latent space feature matching" (2025). Dissertations. 452.
https://louis.uah.edu/uah-dissertations/452
