Name
Abstract | ||
|---|---|---|
This paper presents interim results from an ongoing project on aerial image reconstruction. One important task in image interpretation is the process of understanding and identifying segments of an image. In this effort a knowledge based vision system is being presented, where the selection of IU algorithms and the fusion of information provided by them is combined in an efficient way. In our current work, the knowledge base and control mechanism (reasoning subsystem) are independent of the knowledge sources (visual subsystem). This gives the system the flexibility to add or change knowledge sources with only minor changes in the reasoning subsystem. The reasoning subsystem is implemented using a set of Bayesian networks forming a hierarchical structure which allows an incremental classification of a region given enough time. Experiments with an initial implementation of the system focusing primarily on building reconstruction on three different data sets are presented. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1007/3-540-49256-9_28 | ICVS |
Keywords | Field | DocType |
iu algorithm,image interpretation,visual subsystem,bayesian network,ascender ii,knowledge base,reasoning subsystem,visual framework,change knowledge source,vision system,knowledge source,aerial image reconstruction,3d reconstruction | Iterative reconstruction,Computer vision,Data set,Machine vision,Computer science,Aerial image,Object Class,Bayesian network,Artificial intelligence,Knowledge base,Machine learning,3D reconstruction | Conference |
ISBN | Citations | PageRank |
3-540-65459-3 | 6 | 0.53 |
References | Authors | |
10 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maurício Marengoni | 1 | 96 | 19.02 |
| Christopher O. Jaynes | 2 | 55 | 8.44 |
| A. Hanson | 3 | 1348 | 304.11 |
| E. M. Riseman | 4 | 1402 | 458.95 |