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Accuracy Improvement for Depth from Small Irregular Camera Motions and Its Performance Evaluation

机译:小不规则相机运动的深度精度改进及其性能评估

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We have proposed three-dimensional recovery methods using random camera rotations imitating involuntary eye movements of a human eyeball. Those methods are roughly classified into two types. One is a differential-type using temporal changes of image intensity, and is suitable for coarse textured images relative to the amplitude of the image motion. Another is an integral-type using image blur caused by the camera motions, and is proposed for fine textured images. In this study, we focus on the differential-type method. In this method, it is important that unsuited image pairs for the gradient equation should not be used for computing. We attempt to improve the accuracy by selecting suitable image pairs at each pixel and using only those to recover a depth map. Additionally, we evaluate the performance of the improved method by actually implementing the camera system which can capture images with performing small irregular rotations.
机译:我们已经提出了使用随机相机旋转模拟​​人眼非自愿眼动的三维恢复方法。这些方法大致分为两种类型。一种是利用图像强度随时间变化的差分类型,并且适合于相对于图像运动幅度的粗糙纹理图像。另一个是使用由相机运动引起的图像模糊的积分型,并且提出用于精细纹理图像。在这项研究中,我们着重于差分类型方法。在这种方法中,重要的是不要将不适合用于梯度方程的图像对用于计算。我们尝试通过在每个像素处选择合适的图像对并仅使用那些图像对恢复深度图来提高准确性。此外,我们通过实际实现可通过执行小的不规则旋转来捕获图像的摄像头系统来评估改进方法的性能。

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