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A cube-based saliency detection method using integrated visual and spatial features

发布日期:2016-12-01 18:16:26 阅读次数:[3075]次 作者:

核心提示:来源出版物: SENSOR REVIEW

作者: Liu, T (Liu, Tao); Fang, ZX (Fang, Zhixiang); Mao, QZ (Mao, Qingzhou); Li, QQ (Li, Qingquan); Zhang, X (Zhang, Xing) 
来源出版物: SENSOR REVIEW  卷: 36  期: 2  页: 148-157  DOI: 10.1108/SR-07-2015-0110  出版年: 2016

摘要: Purpose - The spatial feature is important for scene saliency detection. Scene-based visual saliency detection methods fail to incorporate 3D scene spatial aspects. This paper aims to propose a cube-based method to improve saliency detection through integrating visual and spatial features in 3D scenes.

Design/methodology/approach - In the presented approach, a multiscale cube pyramid is used to organize the 3D image scene and mesh model. Each 3D cube in this pyramid represents a space unit similar to a pixel in the image saliency model multiscale image pyramid. In each 3D cube color, intensity and orientation features are extracted from the image and a quantitative concave-convex descriptor is extracted from the 3D space. A Gaussian filter is then used on this pyramid of cubes with an extended center-surround difference introduced to compute the cube-based 3D scene saliency.

Findings - The precision-recall rate and receiver operating characteristic curve is used to evaluate the method and other state-of-art methods. The results show that the method used is better than traditional image-based methods, especially for 3D scenes.

Originality/value - This paper presents a method that improves the image-based visual saliency model.


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