Vizualno sledenje objektov na mobilni platformi

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.