Detecting inactivity segments in E-learning video recordings (DISE)‎

العناوين الأخرى

تحديد المقاطع غير النشطة في فيديوهات المحاضرات في التعليم الإلكتروني

مقدم أطروحة جامعية

Hammu, Sahar S.

مشرف أطروحة جامعية

al-Attar, Ashraf Muhammad

الجامعة

الجامعة الإسلامية

الكلية

كلية تكنولوجيا المعلومات

دولة الجامعة

فلسطين (قطاع غزة)

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2015

الملخص الإنجليزي

Lecture video recordings used in e-learning typically contain segments of inactivity which are better removed in order to save storage and bandwidth load, and to decrease viewing time and effort.

This problem is also common in other areas such as multimedia.

This research proposes a method for detecting segments of inactivity in video sequences and marking them for further processing.

The method is known as DISE.

The core of our approach are two modules one for sound inactivity detection and the other for video inactivity detection.

Inactivity segments detected by the sound module are forwarded to the video module for video inactivity processing.

The method has been developed into a system (DISE) and tested using a collection of real lecture videos obtained from lecture recordings at University of Palestine for different courses under various recording conditions.

The method performs close to human detection as it achieves accuracy of 84.4%.

We believe that our method will add value to the process of recording lectures in the e-learning domain in educational institutes .

التخصصات الرئيسية

العلوم التربوية
تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

عدد الصفحات

84

قائمة المحتويات

Table of contents.

Abstract.

Abstract in Arabic.

Chapter One : Introduction.

Chapter Two : Literature review.

Chapter Three : Related works.

Chapter Four : Methodology and proposed method.

Chapter Five : Experimental results and evaluation.

Chapter Six : Conclusion and future work.

References.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Hammu, Sahar S.. (2015). Detecting inactivity segments in E-learning video recordings (DISE). (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-688588

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Hammu, Sahar S.. Detecting inactivity segments in E-learning video recordings (DISE). (Master's theses Theses and Dissertations Master). Islamic University. (2015).
https://search.emarefa.net/detail/BIM-688588

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Hammu, Sahar S.. (2015). Detecting inactivity segments in E-learning video recordings (DISE). (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-688588

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-688588