一种基于多尺度相谱的显著性检测方法

D. Singh, S. Meher
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引用次数: 0

摘要

显著性检测是集成在各种工业应用中的核心模块之一,如计算机视觉、基于对象的监控、低数据速率系统的内容自适应数据传输。显著性图表示场景中物体的重要性。就像在一个视觉场景中,并不是所有的物体都能得到同样的关注。与周围环境不同的物体会自动获得更多的视觉重要性。基于硬件的眼动仪已经上市,但成本相对较高。因此,为了匹配注视注意力,许多研究者探索了各种算法。提出了一种基于多尺度相谱的显著性检测方法。与其他方法相比,该方法的结果更好,性能更好。分析了四种显著目标检测技术的现状,并与所提出的方法进行了对比,进行了实验评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel approach for saliency detection based on multiscale phase spectrum
Saliency detection is one of the core modules which is incorporated in various industrial applications such as computer vision, object based surveillance, content adaptive data delivery for low data rate systems. Saliency map represents the significance of objects in the scene. As in a visual scene all objects do not get equal attention. Objects which are different from their surroundings, automatically get more visual importance. Hardware based eye tracker devices are commercially available but the cost is comparatively very high. So to match the gaze attention, various algorithms are explored by several researchers. In this paper, multiscale phase spectrum based efficient saliency detection method is proposed. The proposed method is performing better by yielding better results than other methods. Four state-of-art of salient object detection techniques are analyzed along with the ground truth and compared against the proposed method for experimental evaluation.
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