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Jan-Olof Eklundh
Kungl Tekniska Högskolan
Membership Number: 5
Address: NADA/CVAP-CAS, KTH, S-100 44 Stockholm, Sweden
Email: joe@nada.kth.se
Phone:
Fax:
URL: http://www.cas.kth.se

Biographical Sketch
Jan-Olof Eklundh is since 1986 a professor of computer science at KTH, specializing in computer vision and robotics. He graduated in mathematics at Stockholm University, 1970, and then held positions at the Swedish Defense Research Institute, and during 1977-79, at the University of Maryland. In 1982 he joined KTH, where he 1996 was one of the initiators of the Centre for Autonomous Systems. He has been a partner in numerous EU projects, including 6 ESPRIT projects and 2 TMR networks. Professor Eklundh was 1995-99 Dean of the School of Electrical Engineering and Information Technology at KTH. He is a member of the Royal Swedish Academy of Engineering Science and of the Swedish Research Council for Engineering Science. His research interests cover a broad range of topics in computational vision, image processing, and robotics, including behavioural aspects of perception and perceptually guided autonomous systems.

Kungl Tekniska Högskolan (Royal Institute of Technology)
The Computational Vision and Active Perception (CVAP) group at KTH is doing research in computational vision, robotics and related problems in geometric modeling and computing. The group was formed in 1982 and has now almost 30 researchers, graduate students and visiting scientists.

Seeing Robots: A central research theme at CVAP is the development of a computer based seeing agent capable of using vision in its interaction with the environment, for e.g. manoeuvring, navigating, grasping and recognizing things. This work is being implemented as "seeing robots" and addresses basic issues on gaze control, attention, figure-ground segmentation, cue integration, and recognition, as well as systems and control issues.

A second theme that underpins much of this and other work concerns early vision processing and the computation of scene characteristics. Considerable efforts are being devoted to feature and structure extraction at multiple scales. One of the goals is to develop the notion of a visual-front-end, which can provide a first processing layer for the mentioned seeing agent.

Visual Navigation: Another central topic deals with the derivation geometric invariants and their use in deriving scene structure and in tasks such as visual navigation. Properties invariant under perspective and projective transformations can be used to establish image correspondence and to tracking. They also provide a means for model indexing in visual recognition. The latter problem is also studied using other approaches, e.g. based on appearance and also involving learning. The overall goal is to include also these techniques and capabilities in our long-term work on the seeing agent.

In addition to these efforts the group is also developing frameworks and computational environments for performing geometric reasoning and analysis as well as for representing geometric objects such as surfaces and volumes. This work has potential applications in computer vision but is also aimed at the study and teaching of geometry as such.


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