Video based human crowd analysis using machine learning: a survey

ABSTRACT

World population has increased manifolds in the last ten years. With the increase in population at this alarming rate, studying and understanding crowd patterns and their collective behaviour is very important. Researchers from various domains like artificial intelligence, machine learning, social science have shown their interest in understanding crowd phenomena from the social, psychological, and technical points of view. Computer vision techniques play a vital role in developing methods that help in understanding and analysing crowd behaviour automatically. In this article, we have surveyed many models related to crowd analysis developed and employed in computer vision. We aim to provide a comprehensive overview of the research from different aspects of crowd analysis like crowd count, human detection, anomaly detection, human behaviour, the importance of crowd analysis, and recent developments in this field. Major contributions have been included, along with their strengths and limitations.

KEYWORDS:

• Crowd behaviour
• crowd analysis
• crowd features
• crowd tracking
• CNN

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Deevesh Chaudhary

Mr. Deevesh Chaudhary is assistant professor in Information Technology department, School of Computing and IT Manipal University Jaipur. He has completed his M. Tech in CSE from Guru Jambeshwar University of Science and Technology, Hisar, Haryana in 2012. He 6 years of academic experience. He is member of International Association of Engineers. His area of research are computer vision and machine learning.

Sunil Kumar

Dr. Sunil Kumar is professor in Computer and Communication Engineering, School of Computing and IT, Manipal University Jaipur. He has 19 years of academic experience. He completed his M.  Tech. CSE from Kurukshetra University, Kurukshetra in 2002. He has done his PhD in 2015 in image forensics. He has published many articles in international journals and conferences. He is reviewer of many reputed journal published by IEEE, Elsevier, and Springer. He is guiding 06 PhD scholars. He is NVIDIA DLI University ambassador. He is senior member of IEEE, CSI, and ACM. His areas of interest are computer vision, image forensics, and machine intelligence.

Vijaypal Singh Dhaka

Dr. Vijaypal Singh Dhaka is a Professor and Head Dept. of Computer and Communication Engineering ,Manipal University Jaipur, India. His area of research includes Machine Learning, ANN, Pattern Recognition, Medical Imaging Effective Database Communication Strategies and Technology for Social Change. He is an enthusiastic and motivating technocrat with 15 years of research and academic experience. He has hundreds of research papers published in high impact factor journals of SCI indexed, and other reputed journals. His research expertise includes Artificial Intelligence, Pattern recognition and Medical Imaging. He has received 10 IPRs. He authored 6 books and guided 11 research scholars to earn Ph.D. He has organized several international conferences supported by ACM, Springer and Elsevier.