Vision for cognitive robotics and some open meta problems
Event Location: NSH 1507Bio: Michael Zillich received his diploma in Mechatronics from Johannes Kepler University Linz in 1998 and his PhD in Electrical Engineering from Vienna University of Technology in 2007. Michael Zillich is (co)-author of over 80 publications and served on the program committees of a number of international conferences and as reviewer for [...]
Spatial, Temporal and Spatio-temporal Correspondence for Computer Vision Problems
Event Location: GHC 2109Abstract: Many computer vision problems, such as object classification, motion estimation or shape registration rely on solving the correspondence problem. Existing algorithms to solve spatial or temporal correspondence problems are usually NP-hard, difficult to approximate, lack flexible models and mechanism for feature weighting. This proposal addresses the correspondence problem in computer vision, [...]
Wave function representations in shape matching and indexing
Event Location: NSH 3305Bio: Anand Rangarajan has worked in shape analysis for over twenty years. After receiving the Ph.D. from the University of Southern California in 1991, he worked at Yale University in both the radiology and computer science departments until the advent of the new millennium. Since then, he has been in the computer [...]
Learning Through Startups – What They Don’t Teach You in Graduate School
Event Location: NSH 1305Bio: Dr. Dowling is the VP of Engineering for 4moms, a fast-growing Pittsburgh-based company that develops and markets advanced high-tech juvenile products. Previously he was Vice-President of Research and Development at Cambridge-based MC10, Dr. Dowling was responsible for driving MC10's high-performance stretchable electronics technology into products and applications. He built and led [...]
Robust and Efficient Real-time Mapping for Autonomous Robots
Event Location: NSH 1507Bio: Michael Kaess is an Assistant Research Professor in the Robotics Institute at Carnegie Mellon University (CMU). Prior to joining CMU in 2013, he was a Research Scientist (2010-2013) and a Postdoctoral Associate (2008-2010) in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT). He received [...]
Large Scale Visual Recognition in Real-World Images
Event Location: NSH 1507Bio: Jia Li is a research scientist at Yahoo! Research. She leads the Visual Computing and Learning Group. Her research interests are computer vision, machine learning，social network analysis and multimedia analysis. She received her Ph.D. degree from the Computer Science Department at Stanford University. She is the leader of the OPTIMOL team, [...]
Metric Global Localization using Street View
Event Location: GHC 2109Bio: Pratik Agarwal received his B.E. degree in Computer Science and Engineering from Manipal Institute of Technology, India in 2010, and M.S.E. in Computer Science and Engineering from University of Michigan, Ann Arbor in 2012, where he also worked as a research assistant at the APRIL robotics laboratory. Currently, he is a [...]
Presentation and roundtable: Self-sustaining ocean-going robots — and others — and data collection
Event Location: NSH 1305Bio: James Gosling received a BSc in Computer Science from the University of Calgary, Canada in 1977. He received a PhD in Computer Science from Carnegie-Mellon University in 1983. The title of his thesis was "The Algebraic Manipulation of Constraints". He spent many years as a VP & Fellow at Sun Microsystems. [...]
Long-Term Visual Route Following for Mobile Robots
Event Location: NHS 1305Bio: Dr. Timothy Barfoot (Associate Professor, University of Toronto Institute for Aerospace Studies -- UTIAS) holds the Canada Research Chair (Tier II) in Autonomous Space Robotics and works in the area of guidance, navigation, and control of mobile robots for space and terrestrial applications. He is interested in developing methods to allow [...]
State Estimation for Humanoid Robots
Event Location: GHC 8102Abstract: This proposal focuses on dynamic model based state estimation for hydraulic humanoid robots. The goal is to produce state estimates that are robust and achieve good performance when combined with the controller. Three issues are addressed in this proposal. 1. How to handle modelling error using state estimation? 2. How to [...]