结合背景先验和对象先验的显著性检测

doi:10.3969/j.issn.0255-8297.2016.04.010

Abstract

Abstract:

This paper proposes a saliency detection method in which both background prior-based characteristics and object prior-based characteristics are taken into consideration. First, two geodesic saliency maps are generated based on the average color contrast and the EMD distance between two regions represented by the bag of words （BoW）features. A region-level objectiveness map is then generated to measure probability of a region being salient. Finally, a Bayesian classifier is trained to integrate the three saliency maps. The experimental results on ASD and MSRA5000 show that the proposed method outperforms 15 alternative methods.

Key words: saliency detection, featureintegration, objectiveness, background prior, geodesic saliency

CLC Number:

TP399

YUE Ke-juan, ZHENG Ming-cai, XIAO Jian-hua, WU Jiong-xing. Saliency Detection via Combining BackgroundPriors and Object Priors[J]. Journal of Applied Sciences, 2016, 34(4): 451-460.

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Saliency Detection via Combining BackgroundPriors and Object Priors

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