کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
529425 | 869657 | 2014 | 9 صفحه PDF | دانلود رایگان |
• We propose a method to detect visually salient objects in computer rendered images.
• We calculates saliency by measuring object-level contrast.
• Both color and color distribution is considered in contrast computation.
• A new suppression operator is designed.
In this work, we propose a novel graphic saliency detection method to detect visually salient objects in images rendered from 3D geometry models. Different from existing graphic saliency detection methods, which estimate saliency based on pixel-level contrast, the proposed method detects salient objects by computing object-level contrast. Given a rendered image, the proposed method first extracts dominant colors from each object, and represents each object with a dominant color descriptor (DCD). Saliency of each object is then calculated by measuring the contrast between the DCD of the object and the DCDs of its surrounding objects. We also design a new iterative suppression operator to enhance the saliency result. Compared with existing graphic saliency detection methods, the proposed method can obtain much better performance in salient object detection. We further apply the proposed method to selective image rendering and achieve better performance over the relevant existing algorithm.
Journal: Journal of Visual Communication and Image Representation - Volume 25, Issue 3, April 2014, Pages 525–533