This lab has been superseded by the Vision and Mobile Robotics LabOur group studies fundamental problems of 3-D computer vision with a concentration on applications of modeling, recognition, and free-form surface matching. We investigate these problems over a range of physical scales and with a variety of sensors. To efficiently solve surface matching problems, we have developed novel representations, and we are working on algorithms to incorporate machine learning and artificial intelligence techniques into the recognition process.
The domains we consider cover a range of scales, including small-scale object modeling and recognition, medium-scale modeling of building interiors, and large-scale environment mapping and localization. We exploit the fact that many aspects of these problems that are independent of scale, which allows us to use a common base of general algorithms. At the same time, we explore the issues specific to each domain.
From a sensing standpoint, we employ a variety of devices capable of measuring 3-D data. Current sensing systems include desktop laser rangefinders, field-deployable scanning and single-line laser rangefinders (mounted on autonomous vehicles), stereo camera systems, and a 3-D sonar system.
For representing free-form surfaces, we primarily use triangular meshes. Our group has developed new representations to aid in solving surface matching problems, including harmonic maps and spin-image signatures. These representations are examples of surface signatures, meaning they distinctively encode local properties of arbitrary points on a free-form surface.
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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