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Robust depth estimation with occlusion detection using concepts of optical flow

机译:使用光流概念的遮挡检测鲁棒深度估计

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In this paper we present an approach to go beyond the accuracy limits of current optical flow estimators. We have used coarse to over-fine approach along with hybrid interpolation to upgrade coarse to fine approach. Coarse to fine approach is used by most modern optical flow algorithms. Results of suggested method show benefit for sub-pixel motion. It also reduces the estimation error to great extent. Hybrid interpolation method is used which is an integration of bilinear and bi-cubic interpolation methods. Results of our approach on benchmark sequences show that estimated depth map are clearer and boundaries are sharper than original coarse to fine approach with bi-cubic interpolation method. Once optical flow vectors are found occlusion is detected based on the concept of residual error image.
机译:在本文中,我们提出了一种超越电流光学流量估计器的精度限制的方法。我们使用粗糙的方法以及混合插值来升级粗糙到精细的方法。大多数现代光学流量算法使用粗糙到精细方法。建议方法的结果显示子像素运动的益处。它还在很大程度上降低了估计误差。使用混合内插方法,其是双线性和双立方插值方法的集成。我们在基准序列上的方法的结果表明,估计的深度图是更清晰,边界比具有双立方插值方法的原始粗的原始方法更清晰。一旦发现发现光学流量向量,基于残留误差图像的概念检测遮挡。

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