<?xml version="1.0"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://repozitorij.uni-lj.si/IzpisGradiva.php?id=179586"><dc:title>Visual Object Tracking on a Mobile Platform</dc:title><dc:creator>Tenjović,	Dušan	(Avtor)
	</dc:creator><dc:creator>Lukežič,	Alan	(Mentor)
	</dc:creator><dc:subject>object tracking</dc:subject><dc:subject>image segmentation</dc:subject><dc:subject>SAM</dc:subject><dc:subject>DAM4SAM</dc:subject><dc:subject>computer vision</dc:subject><dc:subject>real-time processing</dc:subject><dc:subject>mobile platform</dc:subject><dc:subject>PTZ camera</dc:subject><dc:description>This thesis presents a real-time object segmentation and tracking system integrated into the ViCoS Cube demonstration cell. It implements a segmentationbased tracker DAM4SAM that uses SAM2.1 model combined with a distractoraware memory. The tracker provides precise pixel-level masks and object centroids for closed-loop pan-tilt-zoom (PTZ) camera control. A Docker-based, publish/subscribe architecture using Echolib enables modular integration of camera
streams, tracking, and GUI. The system is evaluated in a controlled environment,
analyzing accuracy, robustness, and speed with different hardware and camera
configurations. Finally, the system’s ability to follow and segment a moving object is demonstrated in real-time, closing the loop between perception and camera
actuation. This project brings cutting-edge segmentation and tracking methods
to an interactive educational setup.</dc:description><dc:date>2026</dc:date><dc:date>2026-02-18 08:00:00</dc:date><dc:type>Diplomsko delo/naloga</dc:type><dc:identifier>179586</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
