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Direct Solution of the Least Squares Matching Problem

机译:直接解决最小二乘匹配问题

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This work presents new approach to matching two images in the case of uncalibrated stereo rig. It is based on the direct use of well known in photogrammetry Least Squares Matching (LSM) technique. The developed algorithm (DLSM -Direct Least Squares Matching) uses modification of the LSM where the disparity map inside each matched window of the reference image is described by the affine transformation. This model accounts local disparity gradients and ensures efficiency of the DLSM for wide baseline stereo. The linear model is used to describe intensity transformation. The LSM is a nonlinear procedure that requires initial approximation of the estimated parameters for each matched window. Here we don't follow the usual practice based on utilization of the intermediate matching algorithms for obtaining such initial approximations. Our strategy is based on prediction of affine and intensity parameters and utilization of the recursive filling procedure to propagate solution of the least squares matching problem on the connected textured areas of the reference image where a smooth disparity map exists. Experimental results on real images are presented to illustrate the robustness and reliability of the DLSM in the case of wide baseline stereo and for matching images containing periodical textures.
机译:这项工作提出了在未校准立体声钻机的情况下匹配两个图像的新方法。它基于直接使用摄影测量最小二乘匹配(LSM)技术。发达的算法(DLSM -direct最小二乘匹配)使用LSM的修改,其中参考图像的每个匹配窗口的视差图描述由仿射变换描述。这种型号帐户本地差异梯度并确保DLSM的宽基线立体声效率。线性模型用于描述强度变换。 LSM是一个非线性过程,需要对每个匹配窗口的估计参数初始近似。在这里,我们不遵循通常的实践,基于利用中间匹配算法来获得这种初始近似。我们的策略基于对仿射和强度参数的预测和递归填充过程的利用率,以传播在参考图像的连接纹理区域上的最小二乘匹配问题的解决方案,其中存在平滑视差图。提出了实验结果的实验​​结果以说明DLSM在宽基线立体声的情况下的鲁棒性和可靠性,以及用于匹配包含周期性纹理的图像。

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