Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast Image Retrieval Algorithm with Automatically Extracted Discriminant Features
CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
Hi-index | 0.00 |
This paper presents an incremental algorithm for classification problems using hierarchical discriminant analysis for real-time learning and testing applications. Virtual labels are automatically formed by clustering in the output space. These virtual labels are used for the process of deriving discriminating features in the input space. This procedure is performed recursively in a coarse-to-fine fashion resulting in a tree, called incremental hierarchical discriminating regression (IHDR) method. Embedded in the tree is a hierarchical probability distribution model used to prune unlikely cases. A sample size dependent negative-log-likelihood (NLL) metric is used to deal with large-sample size cases, small-sample size cases, and unbalanced-sample size cases, measured among different internal nodes of the IHDR algorithm. We report the experimental results of the proposed algorithm for an OCR classification problem and an image orientation classification problem.