Name
Abstract | ||
|---|---|---|
The paper proposes a new spatial extension of Bag-of-Features BoF formalism for classification tasks. The scheme is based on multi-annulus partition which contains much spatial information of image space. Experiments are conducted using final super-vector image representation in Support Vector Machine SVM framework for classification on Oxford flowers and 15 scenes data sets. The results of experiment have shown the effectiveness of our scheme in terms of multiple performance metrics. In addition, our scheme is conceptually simple and easily adoptable. It can lead to much more compact representations and more invariance to image transformation compared to several existing works. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1504/IJSNET.2013.052733 | IJSNET |
Keywords | Field | DocType |
final super-vector image representation,new spatial extension,classification task,support vector machine svm,image space,image transformation,spatial information,compact representation,oxford flower,bag-of-features bof formalism,image classification,support vector machines,svm | Spatial analysis,Data set,Pattern recognition,Invariant (physics),Computer science,Support vector machine,Image representation,Artificial intelligence,Formalism (philosophy),Contextual image classification,Partition (number theory) | Journal |
Volume | Issue | ISSN |
13 | 1 | 1748-1279 |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ye Liang | 1 | 6 | 5.39 |
| Jian Yu | 2 | 1347 | 149.17 |
| Hongzhe Liu | 3 | 56 | 10.93 |
| Zhifeng Xiao | 4 | 199 | 16.26 |