A Novel 3-D Image Retargeting by using Stereo Seam Carving with Disparity Map Acquisition (DMA) Algorithm

M. Jagtap, R. Tripathi
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引用次数: 1

Abstract

Gaining popularity in digital world imposes the challenge to preserve the semantic significances in the original image while display on any arbitrary device irrespective of its size or aspect ratio is the well-known ‘Image Retargeting’. When the image is to be tailored by focusing on its objectives tenacity, then the insignificant portions of the images are identified and wipe out. The historical method envisages the due respect to the pixels by considering its bottom to top style. On the contrary, the projected method builds by using top-down tactic. This appraisal is fused by ‘Classification guided Fusion Network (CFN). The feature is widely applied on 3D images which fuses left as well as right eye images which are having different viewpoints and differently designed. The disparity map acquisition algorithm fuses the images with semantic collage of the images.
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一种基于视差图获取(DMA)算法的立体缝雕刻三维图像重定位方法
在数字世界中越来越受欢迎,这给保留原始图像的语义意义带来了挑战,同时在任何任意设备上显示,无论其大小或宽高比如何,都是众所周知的“图像重定向”。当图像要通过聚焦其目标坚韧度来定制时,图像中不重要的部分被识别并删除。历史方法通过考虑其从下到上的样式来设想对像素的适当尊重。相反,投影方法采用自上而下的策略进行构建。该评价通过分类引导融合网络(CFN)进行融合。该特征广泛应用于具有不同视点和不同设计的左眼和右眼图像融合的三维图像。视差图获取算法将图像与图像的语义拼贴相融合。
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