Tracking an object with a depth-vision camera
Abstract
This thesis focuses on the design and implementation of a system for object detection and tracking using the Intel RealSense D435i depth camera. The main goal is to develop a system that can identify an object in input video stream and track its movement in space. The spatial data obtained from the tracking process are used to control a mobile robotic platform, the Husky A200, via the ROS 2 framework. The theoretical part provides an overview of computer vision methods and algorithms for object detection and tracking. Selected methods were implemented using the OpenCV library and experimentally compared. The results of this project may serve as a foundation for future developments in autonomous robotic platform control systems.
Keywords
Not available
Specialisations
Similar theses
- Distributed Intelligence for 3D Object Tracking in Autonomous Vehicles, A Multi-Sensor Approach to Object Tracking and Planning for Self-Driving Cars, Real-Time 3D Perception and Path Planning in Autonomous Systems,,Vision-Based Localization and Distributed Architecture for Driverless Cars,A Hybrid Deep Learning Framework for Object Detection and Trajectory Planning in Autonomous Vehicles Manas Madine · University of Massachusetts Amherst · 2023
- Study for the vision-based object detection and tracking on unmanned aerial vehicles Eduard Rius Martínez · Universitat Politècnica de Catalunya · 2021
- STABILIZATION AND OBJECT TRACKING BASED ON COMPUTER VISION: APPLICATION IN A QUAD-ROTOR Luis Arreola · 2018
- Biologically Inspired Efficiencies in Computer Vision and Audition Mohammad Kazem Ebrahimpour · 2020
- Design and implementation of a portable machine vision system for real-time object detection and auditory feedback Themba M Sivate · Durban University of Technology · 2026
- Deep Learning-Based Vision System for Intelligent Object Detection and Robotic Sorting Solution Anastasiia Stepanova · Tampere University · 2026
