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Segment-based depth maps extraction from stereo video content

机译:从立体视频内容中提取基于片段的深度图

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In this paper a content-independent, adaptive and parameter-free estimation chain for depth map generation from still-images stereo content will be described. The state-of-the-art solutions for each step of the classical chain will be analyzed as reference benchmark for our proposed implementation. Finally, comparative results will be presented and evaluated through the Middlebury Stereo Evaluation framework to prove the achieved optimal trade-off between quality and computational complexity.
机译:在本文中,将描述用于从静止图像立体内容生成深度图的内容无关,自适应且无参数的估计链。我们将对经典链中每个步骤的最新解决方案进行分析,以作为我们提出的实施方案的参考基准。最后,将通过Middlebury立体声评估框架提供和评估比较结果,以证明在质量和计算复杂度之间实现的最佳折衷。

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