Name
Abstract | ||
|---|---|---|
Many problems in computer vision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image datasets, the high-dimensionality of the data points, that makes the direct application of off-the-shelf learning techniques problematic. In this paper, we present a novel concept class and a companion tractable algorithm for learning a suitable classifier from a given labeled dataset, that is particularly suited to high-dimensional sparse datasets. Each member class in the dataset is represented by a prototype conic section in the feature space, and new data points are classified based on a distance measure to each such representative conic section that is parameterized by its focus, directrix and eccentricity. Learning is achieved by altering the parameters of the conic section descriptor for each class, so as to better represent the data. We demonstrate the efficacy of the technique by comparing it to several well known classifiers on multiple public domain datasets. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/CVPR.2006.20 | Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference |
Keywords | Field | DocType |
supervised learning,novel concept class,member class,conic section classifier,representative conic section,conic section descriptor,data point,prototype conic section,image datasets,new data point,multiple public domain datasets,protocols,face recognition,computer vision,prototypes,biomedical research,feature space,cancer,application software,bioinformatics,information science | Computer science,Artificial intelligence,Classifier (linguistics),Data point,Computer vision,Facial recognition system,Feature vector,Parameterized complexity,Concept class,Pattern recognition,Supervised learning,Conic section,Machine learning | Conference |
Volume | ISSN | ISBN |
1 | 1063-6919 | 0-7695-2597-0 |
Citations | PageRank | References |
1 | 0.36 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arunava Banerjee | 1 | 313 | 29.18 |
| Santhosh Kodipaka | 2 | 4 | 0.76 |
| B.C. Vemuri | 3 | 4208 | 536.42 |