Vishal M. Patel
Friday, March 23, 2018
11 AM - 12 PM
The study of human behavior based on computer vision techniques has gained a lot of interest in recent years. In particular, the behavioral analysis of crowded scenes is of great interest due to a variety of reasons. Exponential growth in the world population and the resulting urbanization has led to an increased number of activities involving high density crowd such as sporting events, political rallies, public demonstrations, thereby resulting in more frequent crowd gatherings in the recent years. In such scenarios, it is essential to analyze crowd behavior for better management, intelligence gathering, safety and security. In this talk, I will present some of my recent work on developing algorithms for crowd analytics, including crowd counting from unconstrained imagery, crowd segmentation and human detection from crowded scenes. I will conclude my talk by describing several promising directions for future research.
Vishal M. Patel is an A. Walter Tyson Assistant Professor in the Department of Electrical and Computer Engineering at Rutgers University. Prior to joining Rutgers University, he was a member of the research faculty at the University of Maryland Institute for Advanced Computer Studies (UMIACS). He completed his Ph.D. in Electrical Engineering from the University of Maryland, College Park, MD, in 2010. His current research interests include signal processing, computer vision, and pattern recognition with applications in biometrics and imaging. He has received a number of awards including the 2016 ONR Young Investigator Award, the 2016 Jimmy Lin Award for Invention, A. Walter Tyson Assistant Professorship Award, Best Paper Award at IEEE AVSS 2017, Best Paper Award at IEEE BTAS 2015, and Best Poster Awards at BTAS 2015 and 2016. He is an Associate Editor of the IEEE Signal Processing Magazine, IEEE Biometrics Compendium, and serves on the Information Forensics and Security Technical Committee of the IEEE Signal Processing Society. He is a member of Eta Kappa Nu, Pi Mu Epsilon, and Phi Beta Kappa.
Dr. Arun Ross