2nd PyData-Cairo Meetup: The Role of Thermal Imaging in Crowd Counting & Control

Welcome to our 2nd Meetup! It's our pleasure to invite you to a talk titled: "The Role of Thermal Imaging in Crowd Counting & Control, the Most Recent findings", hosted by Optomatica, A Machine Learning & Data Science Company, and "Human Foundation", a non-profit Egyptian organization.

Abstract:
A general well-known definition for crowd is a large number of persons gathered closely together and having something in common. Crowds can be classified into two main categories: static crowds and dynamic crowds. Crowd estimation or counting is a technique used to count or estimate the number of people in a crowd. It is a very challenging issue specially for open areas or outdoor scenes. For many events, especially political rallies, protests and religious events, overcrowding and difficulties in crowd control have resulted in a number of fatal accidents. Crowd counting or density estimation and management techniques are necessary to provide complete safety for people in the crowd. Along the history of human beings there were many events that gathered people in very huge crowds. The main reason has always been political in some manner although each one is different owing to place, motivation, and culture. However, the one of the biggest annual crowds in the whole world is the Hajj, the Islamic event that gathers people from every place on earth in a specific time of the year, and in specific places in Saudi Arabia. Hajj gathers around 3,000,000 Muslims yearly to perform rites of pilgrimage. Many studies of automatic crowd counting using depth cameras were conducted in recent years in order to detect big gatherings in outdoor scenes and accordingly avoid accidents but occlusions and unnecessary color information were vital challenges. Researches moved later to count on motion analysis but another problem appeared, which can be summarized in the question: What if not all humans in the crowd are moving? These challenges made researches shift to use thermal imaging in the field of pedestrian detection and crowd counting, as it only relies in the heat characteristics and convert this heat information to an image. The most recent study conducted to measure crowd density from thermal videos captured by infrared cameras attached in Makkah during the event of Hajj will be discussed and compared with the equivalent approaches in literature. The proposed approach combines heat characteristics and motion information together not only to accurately measure the crowd size but also to classify it to moving, static, or mixed crowd.

Speaker's Bio:
Nermin Kamal Negied is a Lecturer at Zewial City, Faculty of Communication & Information Engineering. She was the Educational Quality Manager at MSA, Faculty of Computer Science and a member in the International Accreditation team, a lecturer and graduation projects supervisor at the same university. Nermin was a Lecturer Assistant at 6th of October University, Faculty of Engineering, Computer Engineering department from Sep. 2012 - Sep. 2015, and a Teaching Assistant at the from Sep. 2006 - Sep. 2012.

She got her Ph.D. in Jul. 2016, from Cairo University, Faculty
of Engineering, Computer Department. She got her M.Sc. degree in Feb. 2012, from the same place. Nermin published 11 international journal and conference papers, and shared in reviewing many scientific papers. Her research interests include Image Processing and Computer Vision, Machine Learning, AI, Expert systems, Natural Language Processing, and Genetic Algorithms. She is Currently supervising 3 M.Sc. theses at Faculties of Engineering, Cairo Univ., Monufeya Univ. and AASTM.

Schedule:
12:00 - 12:30 PM - Intro & refreshments
12:30 - 1:30 PM - Dr. Nermin Negied Presentation
1:30 - 2:00 PM - Discussion & Closing

Location:
Building 3, 6th Tourist District
6th of October, Egypt

Location Map: (check also event photos)
http://goo.gl/maps/FeWHptQsgPL2

Note: RSVP is a must.

For any questions, please contact us through PyData-Cairo Meetup Messages