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

Detection of Multiple Salient Objects by Categorizing Regional Features

Vol. 10, No. 1, January 30, 2016
10.3837/tiis.2016.01.016, Download Paper (Free):

Abstract

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.


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]
K. Oh, S. Kim, Y. Kim and Y. Lee, "Detection of Multiple Salient Objects by Categorizing Regional Features," KSII Transactions on Internet and Information Systems, vol. 10, no. 1, pp. 272-287, 2016. DOI: 10.3837/tiis.2016.01.016.

[ACM Style]
Kang-Han Oh, Soo-Hyung Kim, Young-Chul Kim, and Yu-Ra Lee. 2016. Detection of Multiple Salient Objects by Categorizing Regional Features. KSII Transactions on Internet and Information Systems, 10, 1, (2016), 272-287. DOI: 10.3837/tiis.2016.01.016.