Hybrid Simultaneous Localization and Map Building:
A Natural Integration of Topological and Metric
- Environment Modeling
- Localization and Map Building
- Experimental Results
- Conclusions and Outlook
In this talk, I will briefly review the major features of one model of collaborative planning, SharedPlans (Grosz and Kraus, 1996,1999), and will describe efforts to develop collaborative planning agents and systems for human-computer communication based on this model. The model also provides a framework in which to raise and address fundamental questions about collaboration and the construction of collaboration-capable agents. In this context, I will discuss recent approaches to commitment management and group decision-making.
Barbara J. Grosz is Higgins Professor of Natural Sciences in the Division of Engineering and Applied Sciences and Dean of Science of the Radcliffe Institute for Advanced Study at Harvard University. Professor Grosz is known for her seminal contributions to the fields of natural-language processing and multi-agent systems. She developed some of the earliest and most influential computer dialogue systems and established the research field of computational modeling of discourse. Her work on models of collaboration helped establish that field of inquiry and provides the framework for several collaborative multi-agent systems and human-computer interface systems. She has been elected to the American Philosophical Society and the American Academy of Arts and Sciences. She is a Fellow of the American Association for Artificial Intelligence, the ACM, and the American Association for the Advancement of Science, recipient of the University of California at Berkeley Computer Science and Engineering Distinguished Alumna Award and of awards for distinguished service from major AI societies. She is also widely respected for her contributions to the advancement of women in science.
Speaker: Matthew Antone , BAE Systems Advanced Information Technologies
Date: Wednesday, October 19 2005
The past decade has seen great advances in the theory and practice of computer vision. As algorithm maturity and computational power have grown, so also has the demand for robust application of vision techniques in real-world, deployed systems. In the first part of this talk, I will present high-level overviews of a few video-based projects currently under development in our research group. These include tracking of vehicles and people from stationary and moving cameras, and extraction of salient features for object recognition and classification, with emphasis on the implementation of working prototypes.
Camera calibration is vital to the success of many such applications. For example, rectification of perspective effects normalizes size and velocity measurements, while recovery of pose situates disparate cameras and objects in a consistent coordinate frame. However, physical access to the site or to the sensors may be limited, precluding use of explicit calibration patterns. The second part of the talk will describe efficient techniques for automatic recovery of camera intrinsic and extrinsic parameters based upon phenomena observed over time, including object trajectories and cast shadows.