The University of Tennessee
Knoxville, TN 37996-2100
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IRIS Research Staff |
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Sreenivas Rangan Sukumar, M.S Student |
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Office: | 401 Science
& Engineering Building The University of Tennessee Knoxville, TN 37996-2100 |
| Telephone: | (865) 974-9213 | ||
| Fax: | (865) 974-5459 | ||
| E-mail: | rangan@imaging.utk.edu | ||
| Personal Web Page: | http://web.utk.edu/~ssrangan |
| Current Work | ||
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Informational Approach to Shape Description Our approach to shape description burgeons from the seminal work of Shannon. We propose that shapes (of man made objects) can be described as piecewise smooth parts each of which can be uniquely identified using a shape number. We compute the shape number of a surface as the entropy of the curvature density. We segment the parts using a simple region growing procedure and in the future would like to automate this process using the Minima Rule algorithm. Our goal is to describe laser scanned automotive parts and be able to perform similarity search of available CAD models of the automotive components. We believe we would be able to use the part-based description of objects for detection. |
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Laser Scanning for Surveillance & Reverse Engineering The goal of the under vehicle inspection project is to develop mobile robots capable of inspecting a large number of vehicles for concealed nuclear, chemical, and biological weapons. The robot is to be designed with capabilities to capture video, thermal, and range data for threat assessment. Data acquisition is one of the major challenges in this venture and we propose to collect range data from under the vehicle using a sheet of light laser triangulation system. We extend the capability of our sensor system to scan the scene under the vehicle as a color/thermal textured 3D model, suitable for model matching algorithms. Reverse engineering is the process of duplicating an existing component by extracting its physical dimensions. It is almost impossible to get replacements for certain obsolete automobile components. We generate 3D CAD models of such an object of interest by reconstructing the point cloud output of 3D scanners. Our procedure reverse engineers the geometry but not functionality. |
| Previous Work | ||
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We have implemented an algorithm to measure the shape complexity for discrete approximations of planar curves and manifold surfaces. We base our algorithm on a curvature definition of shape, and thus we compute shape information as the entropy of curvature. We present definitions to estimate curvature for both discrete curves and surfaces and formulate our theory of shape information from these definitions. We demonstrate our algorithm with a set of triangle mesh models and discuss relevant applications in 3D Surface Registration and Model based object discrimination. |
