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Conference Paper
Target Tracking via Region-Based Confidence Computation with the CNN-UM
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- Authors
- Hyong-suk Kim, Hong-rak Son, Young-jae Lim, Jae-chul Chung
- Issue Date
- 2002-12
- Citation
- Pacific Rim Conference on Multimedia (PCM) 2002 (LNCS 2532), pp.775-782
- Publisher
- Springer
- Language
- English
- Type
- Conference Paper
- 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.
- KSP Keywords
- CNN-UM, Computational systems, Confidence value, ITS region, Parallel Processing, Region-based, Tracking algorithm, computational structure, each region, fusion algorithm, target tracking