Master's Thesis
Detection and Tracking in Airborne Image Sequences
— 2018
Key information
Authors:
Supervisors:
Published in
June 26, 2018
Abstract
This work proposes and evaluates a method for detection and tracking of maritime vessels in airborne image sequences. Such sequences are challenging due to sun reflections, low resolution, wakes, wave crests and fast motions either from the vessel but also from the UAV (Unmanned Aerial Vehicle), which significantly degrade the performance of general purpose tracking algorithms. The proposed method is based on state-of-the-art deep neural network detection method complemented with a correlation filter tracker. We evaluate our proposal using a known benchmark in the field and compare the obtained results with the results obtained with the original algorithms. The dataset used to perform the evaluations was obtained during the SEAGULL project.
Publication details
Authors in the community:
Patrícia Maria Gonçalves Silva
ist170411
Supervisors of this institution:
Fields of Science and Technology (FOS)
mechanical-engineering - Mechanical engineering
Publication language (ISO code)
por - Portuguese
Rights type:
Embargo lifted
Date available:
April 30, 2019
Institution name
Instituto Superior Técnico