A vision-based object tracking system for weight sensitive unmanned systems

العناوين الأخرى

نظام تتبع بصري للمنظومات الذكية حساسة الوزن

مقدم أطروحة جامعية

Abu Ghaliyah, Karam Mahmud Hasan

مشرف أطروحة جامعية

Sababhah, Bilal

أعضاء اللجنة

al-Qarallah, Isam Ata Allah Y.
Rawashidah, Nadhir
al-Haj, Ali

الجامعة

جامعة الأميرة سمية للتكنولوجيا

الكلية

كلية الملك عبدالله الثاني للهندسة

القسم الأكاديمي

قسم الهندسة الكهربائية

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2016

الملخص الإنجليزي

Object detection and tracking are significant and complex tasks in the field of computer vision.

This field has many applications like surveillance as in detecting abandoned bags in airports or tracking a suspect, vehicle navigation, and autonomous robot navigation for unmanned vehicles or industrial robots.

Object tracking and detection in surveillance videos for humans, vehicle or any other object is a challenging research topic in computer vision; especially in a dynamic environment and non-static cameras.

Non-static cameras involves more challenges in motion classification.

Those challenges rise due to the virtual moving of the whole scene.

Object tracking and detection are essential technologies to fight against terrorism, crimes and for traffic management.

The ability of detecting and tracking targets could also play a significant role in robots’ navigation systems.

Visual tracking systems may issue the direction and speed of motion to the robot to keep the target in its angle of view either by moving the robot itself or the vision sensors.

In this work, a compact size tracking and guiding system that could be mounted on UAV platforms is presented.

The system combines a motion detection technique that could be used with non-static cameras in addition to color filtering to detect and track objects in the field of UAV view.

This hybrid system provides a more reliable tracking system.

The proposed system implements algorithms from literature in a hybrid approach that utilizes the best of each algorithm and avoids heavy resources usage.

Experimental tests showed the system’s ability to detect and track low detailed targets.

The system also showed flexible optimization for speed, as it is possible to keep tracking target objects even with frame skipping giving real-time processing.

التخصصات الرئيسية

الهندسة الكهربائية

عدد الصفحات

67

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-693682