Bharath’s main research interests include pattern recognition and computer vision. At present, his research is centered on event-based cameras for autonomous sensing and navigation. This includes tracking and recognition with an array of sensors, most importantly event-based cameras, to be processed efficiently on low-power devices to yield accurate results at real-time. In the past, he has mostly worked on object recognition and related areas such as scene understanding, face recognition, and object detection. He received the B.E. degree in electrical & electronics engineering from Anna University of India in 2009; M.Sc. and Ph.D. degrees in electrical engineering from National University of Singapore in 2011 and 2015 respectively, working at the Control and Simulation Laboratory on Image Classification using Invariant Features.
As an extremely hot research topic, computer vision has found broad applications in Unmanned Aerial Vehicles (UAVs), such as vision-based navigation, object detection, identification and tracking. Nowadays, there has been a growing interest in inexpensive small UAVs for military and civil applications. In particular, area surveillance and higher-level vision tasks have drawn most of attention with a focus on low-power sensing capabilities. This talk reviews the fundamentals and properties of object recognition by leveraging exciting technologies including silicon retina sensors and low-power processing devices. The second part of the talk focuses on the development of an event-based algorithm to tackle the problem of object tracking with a moving event camera. We provide a unified view of the main approaches for event-based sensing on low-power FPGA devices under closed-loop control. Lastly, we discuss open problems to build bio-inspired embedded sensory systems for autonomous navigation of aerial vehicles and remote sensing applications.
Time: 22 May, Wednesday, 2019, 10:00-11:00AM
Host: Dr. Shiyu Zhao, School of Engineering
Venue: Lecture Hall, 1st Floor, Build 5, Yunqi Campus