The Robotics Institute

Carnegie Mellon Robotics Institute

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		Takeo Kanade U.A. and Helen Whitaker University Prof., RI/CS Email: Office: NSH 4119 Phone: (412) 268-3016 Fax: 412-268-5570   Mailing address: Carnegie Mellon University Robotics Institute 5000 Forbes Avenue Pittsburgh, PA 15213 Administrative Assistant: Suzette Mongell Gambone Affiliated Center(s):  Vision and Autonomous Systems Center (VASC)  Quality of Life Technology Center (QoLT)  Medical Robotics Technology Center (MRTC) Personal Homepage

Current Labs & Groups [ Past Labs & Groups]
		Component Analysis The Component Analysis Lab is devoted to research new learning techniques to encode and decompose a given signal into relevant components for classification, clustering, modeling and visualization.
		Computational Sensor Laboratory We are developing specialty imaging sensors for improving robustness and capabilities of robot vision systems.
		Face Group Robust detection, recognition, and tracking of human faces with automated analysis of expressions
		Helicopter Lab A vision-guided robot helicopter which can function in any weather conditions using only on-board intelligence and computing power.
		Human Identification at a Distance (HumanID) We are developing and evaluating human identification technologies as part of the Defense Advanced Research Projects Agency (DARPA) sponsored program in Human Identification at a Distance (HumanID).
		Medical Robotics and Computer Assisted Surgery (MRCAS) Researching planning (medical image computing, simulation) and execution (intraoperative sensing and actuation) technologies for computer-assisted surgery.
		People Image Analysis Consortium (PIA) The People Image Analysis (PIA) Consortium develops and distributes technologies that process images and videos to detect, track, and understand peoples' faces, bodies, and activities.
		Video Surveillance and Monitoring Coordinated video surveillance system
		Virtualized RealityTM Construct views of real events from nearly any viewpoint
		Vision for Safe Driving Computer vision algorithms and systems for automotive safe driving applications.
		Vision for Virtual Environments Using techniques from computer vision and robotics, we are developing novel sensing and display technologies to support practical, useful virtual environments.