• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Bag of Visual Words Method based on PLSA and Chi-Square Model for Object Category


Abstract

The problem of visual words。ッ synonymy and ambiguity always exist in the conventional bag of visual words (BoVW) model based object category methods. Besides, the noisy visual words, so-called 。ーvisual stop-words。ア will degrade the semantic resolution of visual dictionary. In view of this, a novel bag of visual words method based on PLSA and chi-square model for object category is proposed. Firstly, Probabilistic Latent Semantic Analysis (PLSA) is used to analyze the semantic co-occurrence probability of visual words, infer the latent semantic topics in images, and get the latent topic distributions induced by the words. Secondly, the KL divergence is adopt to measure the semantic distance between visual words, which can get semantically related homoionym. Then, adaptive soft-assignment strategy is combined to realize the soft mapping between SIFT features and some homoionym. Finally, the chi-square model is introduced to eliminate the 。ーvisual stop-words。ア and reconstruct the visual vocabulary histograms. Moreover, SVM (Support Vector Machine) is applied to accomplish object classification. Experimental results indicated that the synonymy and ambiguity problems of visual words can be overcome effectively. The distinguish ability of visual semantic resolution as well as the object classification performance are substantially boosted compared with the traditional methods.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
Yongwei Zhao, Tianqiang Peng, Bicheng Li and Shengcai Ke, "Bag of Visual Words Method based on PLSA and Chi-Square Model for Object Category," KSII Transactions on Internet and Information Systems, vol. 9, no. 7, pp. 2633-2648, 2015. DOI: 10.3837/tiis.2015.07.017

[ACM Style]
Zhao, Y., Peng, T., Li, B., and Ke, S. 2015. Bag of Visual Words Method based on PLSA and Chi-Square Model for Object Category. KSII Transactions on Internet and Information Systems, 9, 7, (2015), 2633-2648. DOI: 10.3837/tiis.2015.07.017