Dr. Dan Levi

Dr. Dan Levi

Staff Researcher
General Motors

Bio:

I received my B.Sc. degree (with honor) in mathematics and computer science from the Tel-Aviv University, in 2000, and the M.Sc. and PhD degrees in applied mathematics and computer science at the Weizmann Institute, in 2004 and 2009 respectively. In the Weizmann Institute I conducted research in human and computer vision under the supervision of Professor Shimon Ullman. Since 2007 I have been conducting industrial computer vision research and development at several companies including General Motors and Elbit Systems, Israel.

Title:

Training Models for Road Scene Understanding with Automated Ground Truth

Abstract:

Collecting and labeling training data for vision-based road scene understanding is a major challenge. The most prominent approach is to use manual labeling, though it is clear that scalability of this approach is limited. More scalable alternatives are simulated data and cross-sensor label transfer. In this talk I will present automatically generated ground truth using one or more sensors, primarily dense Lidar. Specifically, I will present the benefits and challenges of this approach for road scene understanding tasks, including general and category-based obstacle detection, free space and curb detection.