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Proceedings Paper

New method for sensor data fusion in machine vision
Author(s): Yuan-Fang Wang
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Paper Abstract

In this paper, we propose a new scheme for sensor data fusion in machine vision. The proposed scheme uses Kalman filter as the sensor data integration tool and hierarchical B- spline surface as the recording data structure. Kalman filter is used to obtain statistically optimal estimations of the imaged surface structure based on external sensor measurements. Hierarchical B-spline surface maintains high-order surface derivative continuity, may be adaptively refined, possesses desirable local control property, and is storage efficient. Hence, it is used to record the reconstructed surface structure.

Paper Details

Date Published: 1 September 1991
PDF: 12 pages
Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991); doi: 10.1117/12.49973
Show Author Affiliations
Yuan-Fang Wang, Univ. of California/Santa Barbara (United States)


Published in SPIE Proceedings Vol. 1570:
Geometric Methods in Computer Vision
Baba C. Vemuri, Editor(s)

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