Name
Title | ||
|---|---|---|
Towards Effective Image Classification Using Class-Specific Codebooks and Distinctive Local Features |
Abstract | ||
|---|---|---|
Local image features, which are robust to scale, view, and orientation changes in images, play a key factor in developing effective visual classification systems. However, there are two main limitations to exploit these features in image classification problems: 1) a large number of key-points are located during the feature detection process, and 2) most of the key-points arise in background regions, which do not contribute to the classification process. In order to decrease the inverse effects of these limitations , we propose a new codebook generation approach through employing a new clustering method that generates class-specific codebooks along with a novel feature selection method in the bag-of-words model. We evaluate the performance of different classification techniques including Naive Bayesian, k-NN, and SVM on distinctive features. Experiments conducted on PASCAL Visual Object Classification collections have shown that the class-specific codebooks along with distinctive image features can significantly improve the classification performances. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TMM.2014.2388312 | Multimedia, IEEE Transactions |
Keywords | Field | DocType |
feature extraction,feature selection,image classification,pattern clustering,support vector machines,svm,bag-of-words model,class-specific codebook generation,clustering method,distinctive local feature,feature selection method,k-nn,naive bayesian,bag-of-words,class-specific codebooks,distinctive local features,self-organizing maps,self organizing maps,visualization,bag of words model,histograms,bag of words,computational modeling | Feature selection,Computer science,Artificial intelligence,Cluster analysis,Contextual image classification,Computer vision,Bag-of-words model in computer vision,Pattern recognition,Naive Bayes classifier,Feature (computer vision),Support vector machine,Machine learning,Codebook | Journal |
Volume | Issue | ISSN |
17 | 3 | 1520-9210 |
Citations | PageRank | References |
5 | 0.40 | 17 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Umit Lutfu Altintakan | 1 | 5 | 0.40 |
| Adnan Yazici | 2 | 649 | 56.29 |