Title: An Introduction to Point Cloud Understanding
Brian VanVoorst, MTU Alumni & Technical Director of BBN Technologies
Thursday, March 22,2012 – 135 Fisher Hall – 2:00 PM
Abstract: A point cloud is a collection of 3D points from a 3D sensor such as a LIDAR, stereo camera, or a Microsoft Kinect system. These 3D sensors are used in applications of robotics, mapping (such as the Google Street View platforms), and entertainment. At BBN there are multiple projects under way with a common theme of “point cloud understanding.” Point cloud understanding is an area of computer vision research in which algorithms are developed to extract knowledge from point clouds. In this talk an overview of 3D sensors and their point clouds, discuss challenges computer scientists face in processing point clouds, explain some of the key algorithms and data structures, highlight the differences between point cloud understanding and image understanding, and explore opportunities for sensor fusion. I will draw heavily upon the real-world challenges we face in our ongoing research projects. This talk will be accessible to computer scientists and engineers at all levels.
Biography: Brian VanVoorst joined BBN Technologies in 2008 as a Technical Director to help form the BBN Technologies office in Minnesota. He has more than 19 years of experience working on and leading research and development programs. His most recent work is in the area of the automated understanding of LIDAR point clouds. His previous work has been in many areas, including real-time and fault-tolerant systems, mobile ad-hoc networking, parallel processing, and parallel system benchmarking. He also has worked extensively with robotics and was part of a team that was a finalist for the DARPA Urban Challenge. Before coming to BBN, VanVoorst was a researcher at Honeywell Labs for 14 years and spent two years at the NASA Ames Research Center. VanVoorst earned his bachelor’s and master’s degrees in computer science from Michigan Technological University. From 1999–2001 he held a lectureship position at Michigan Tech and taught in the Computer Science Department while continuing to work for Honeywell. He holds one patent with four applications pending and has published more than 20 papers in conference proceedings and journals.