/Daniel Huber

Daniel Huber

Portrait of Daniel Huber
Adjunct Faculty
Phone: (412) 268-3818
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My area of expertise is three dimensional (3D) computer vision, specifically using high accuracy range sensors such as laser scanners for problems in the areas of modeling, recognition, and visualization. My goal is to make progress toward solving the problem of scene understanding using 3D computer vision. I am particularly interested in methods that combine image-based approaches from traditional computer vision with 3D computer vision algorithms. I am interested in methods to extract high-level semantics from 3D models, such as models of buildings. The ability to reverse engineer buildings has enormous potential benefit in a variety of fields, ranging from robotics to civil engineering to homeland security. I am also interested in methods for processing and visualizing 3D data in real time for high-speed teleoperation telepresence applications. Finally, I am studying the effects of sensor noise and data artifacts on the accuracy of 3D models for precision measurement applications.

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