Publication Type |
Journal Article |
School or College |
College of Engineering |
Department |
Computing, School of |
Creator |
Henderson, Thomas C. |
Other Author |
Fai, Wu So |
Title |
Pattern recognition in a multi-sensor environment |
Date |
1983 |
Description |
Current pattern recognition systems tend to operate on a single sensor, e.g., a camera. however. the need is now evident for pattern recognition systems which can operate in multi-sensor environments. For example, a robotics workstation may use range finders. cameras, tactile pads, etc. The Multi-sensor Kernel System (MKS) provides an efficient and coherent approach to the specification, recovery, and analysis of patterns in the data sensed by such a diverse set of sensors. We demonstrate how much a system can be used to support both feature-based object models as well as structural models. The problems solved is the localization of a three-dimensional object in 3-space. Moreover, MKS allows rapid reconfiguration of the available sensors and the high-level models. |
Type |
Text |
Publisher |
University of Utah |
First Page |
1 |
Last Page |
36 |
Subject |
Pattern recognition; Multi-sensor; Multi-sensor Kernel System; MKS |
Subject LCSH |
Multisensor data fusion |
Language |
eng |
Bibliographic Citation |
Henderson, T. C., & Fai, W. S. (1983). Pattern recognition in a multi-sensor environment. 1-36. UUCS-83-001. |
Series |
University of Utah Computer Science Technical Report |
Rights Management |
©University of Utah |
Format Medium |
application/pdf |
Format Extent |
4,930,219 bytes |
Identifier |
ir-main,15996 |
ARK |
ark:/87278/s61z4p08 |
Setname |
ir_uspace |
ID |
706648 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s61z4p08 |