Name
Abstract | ||
|---|---|---|
A target tracking algorithm with the region-based confidence computation on the CNN-UM is proposed. The CNN-UM is an analog parallel computational system which handles regions easily with its region creating capability, parallel processing in the region and regional constraining capability. If the probability for each feature is created in each region, the total confidence of a target can be computed with a fusion algorithm employing products of weighted sums of feature probabilities. The cell-wise target decision in the region can be performed depending on the confidence value at each cell. By virtue of the analog parallel computational structure of the CNN-UM, the computation speed is very fast. On chip experimental results are included in this paper. |
Year | Venue | Keywords |
|---|---|---|
2002 | IEEE Pacific Rim Conference on Multimedia | target tracking,computation speed,total confidence,region-based confidence computation,analog parallel computational system,parallel processing,feature probability,target tracking algorithm,confidence value,cell-wise target decision,analog parallel computational structure,chip,parallel computer |
Field | DocType | Volume |
Pattern recognition,Computer science,Parallel processing,Image processing,Algorithm,Artificial intelligence,Interconnection,Artificial neural network,Cellular neural network,Image sequence,Computation | Conference | 2532 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-00262-6 | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyongsuk Kim | 1 | 500 | 64.95 |
| Hongrak Son | 2 | 22 | 4.75 |
| Youngjae Lim | 3 | 2 | 1.77 |
| Jae-chul Chung | 4 | 0 | 0.34 |