Eshed Ohn-Bar
Postdoctoral Researcher, University of California, San Diego

Abstract
The goal of my research is to develop human-centered algorithms for intelligent and autonomous systems. The research emphasizes modeling the perception, intent, and behavior of humans inside and around a vehicle. Over a decade has passed since the DARPA Grand Challenges, and the way in which we transport people and goods has yet to radically change. That is why I work to disrupt and transform transportation systems, with the urgent outcome of reduction in road traffic injuries and development of assistive technologies. The future of scalable and affordable self-driving cars is excitingly near!

My goal for this talk is to analyze human activities in the context of driving, navigation, and collaboration. I will discuss vision and learning algorithms for semantic video analysis, attention and situational awareness modeling, human state and style recognition, and event anticipation. I will propose holistic multi-modal (cameras, radar, lidar, IMU/GPS), multi-cue (driver/pedestrian body pose, head, hand, foot) frameworks in order to answer two predictive safety related questions: what is going to happen in a scene in the near future? and, which of the surrounding agents are most relevant to the navigation task? An approach for modeling and evaluating the complex interplay between maneuvering task, object attributes, scene context, intent, and future scene state will take us a step closer towards a safe, enjoyable, and personalized driving experience.

Speaker Biography
Eshed Ohn-Bar is a postdoctoral researcher in the Computer Vision and Robotics Research (CVRR) lab and the Laboratory for Intelligent and Safe Automobiles (LISA) at UCSD. Eshed is interested in machine vision and learning, with a focus on recognition and understanding of human behavior for intelligent and interactive environments. He helped organize four workshops on understanding hand activity at CVPR (2015, 2016) and the IEEE Intelligent Vehicles Symposium (2015, 2016). He received the best paper award at the workshop on Analysis and Modeling of Faces and Gestures 2013, best industry related paper finalist at ICPR 2014, and best Piero Zamperoni student paper award finalist at ICPR 2016. Eshed received the B.S. degree in mathematics from UCLA in 2010, and the Ph.D. degree in electrical engineering from UCSD in 2016.