Saliency detection via background features

Wei Jiang; Houde Dai; Yadan Zeng; Mingqiang Lin

doi:10.1117/12.2503198

9 August 2018 Saliency detection via background features

Wei Jiang, Houde Dai, Yadan Zeng, Mingqiang Lin

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108060T (2018) https://doi.org/10.1117/12.2503198
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

The background information is full of essential clues which could be used to distinguish the foreground from images, especially when images contain multiple targets or complex backgrounds. In this paper, we formulate the saliency detection task as a labelling problem. We propose a novel saliency detection method via fusing a set of features based on background information. We firstly extract background features referred to as uniqueness feature, dense feature, and sparse feature. Specifically, uniqueness feature is defined using the color distinction and spatial distance based on the K-means algorithm; dense feature of the background segments is calculated by the PCA algorithm; sparse feature is computed based on the sparse encode algorithm. Then we fuse these background features under the CRF frame. Finally, we evaluate our proposed method on a new constructed dataset from THUS10000, SOD and ECSSD datasets to cover different scenarios. The experimental results show that our method can be well against the previous methods in terms of precision and recall.

Citation Download Citation

Wei Jiang, Houde Dai, Yadan Zeng, and Mingqiang Lin "Saliency detection via background features", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108060T (9 August 2018); https://doi.org/10.1117/12.2503198

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