Main Page
Deanship
The Dean
Dean's Word
Curriculum Vitae
Contact the Dean
Vision and Mission
Organizational Structure
Vice- Deanship
Vice- Dean
KAU Graduate Studies
Research Services & Courses
Research Services Unit
Important Research for Society
Deanship's Services
FAQs
Research
Staff Directory
Files
Favorite Websites
Deanship Access Map
Graduate Studies Awards
Deanship's Staff
Staff Directory
Files
Researches
Contact us
عربي
English
About
Admission
Academic
Research and Innovations
University Life
E-Services
Search
Deanship of Graduate Studies
Document Details
Document Type
:
Thesis
Document Title
:
Video Analysis for Abnormal Human Behavior in The examination Room
تحليل تصرف الانسان باستخدام الفيديو في غرفة الاختبارات
Subject
:
Faculty of Computing and Information Technology
Document Language
:
Arabic
Abstract
:
The anomalous behavior is hard to be detected simultaneously in a complex scene such as detecting abnormal movements of examinees in examination rooms. Modeling activities of moving objects and classifying them as normal or anomalous is a major research problem in video analysis. In this thesis, we make use of the Neural Networks and Gaussian distribution to help solve this problem by building a prototype of a monitoring system that consists of three stages; face detection using Haar cascade detector, suspicious state detection using a neural network and lastly anomaly detection based on the Gaussian distribution. The main idea is to decide on whether the student is in a suspicious state or not using a trained neural network and then decide that a student performs an anomalous behavior based on how many times he was found in a suspicious state in a defined time duration. The type of cheating that we will detect in our systems will include looking at other students’ papers or if the student moved his/her head to look right, left, up or down. The complete system has been tested on a proprietary data set achieving 97% accuracy with 3% false negative rate.
Supervisor
:
Dr. Mohamed Dahab
Thesis Type
:
Master Thesis
Publishing Year
:
1440 AH
2018 AD
Co-Supervisor
:
Dr. Gabriel Abu Samra
Added Date
:
Sunday, December 9, 2018
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
أسماء إبراهيم آل إبراهيم
Al Ibrahim, Asma Ibrahim
Researcher
Master
Files
File Name
Type
Description
43846.pdf
pdf
Back To Researches Page