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A new composite multi-constrained differential-radon warping approach for digital video affine motion stabilization

机译:一种用于数字视频仿射运动稳定的新型复合多约束微分rad变形方法

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This paper presents a new projection based affine motion stabilizer framework for video stabilization using differential-Radon (DRadon) curve warping. Extending the translational domain of classical projection based algorithms towards affine stabilization, multiple angular curves obtained with Radon or rotated images have recently been explored for combined rotation and zoom estimation. Radon provides efficient projection extraction, but use of integral intensity under local variation degrades the desired motion accuracy. DRadon works on derivative of each angular slice to incorporate shape based matching for better projection alignment. Based on human perception of inter-frame tilt in unsteady camera recordings, the proposed angular DRadon curve estimation is confined to angular search space of [-20°, 20°] with the angular increment of 0.1°. Out of complete set of angular DRadon curves of reference frame, five key-angular slices are selected and correlated with their corresponding neighbourhood in target DRadon for inter-frame tilt estimation. Best matched key slices of reference and target DRadon are warped using a novel multi-constrained approach and the extracted warping vectors are further processed for translation and zoom estimation. A vector-slope algorithm based on relative stretching/contraction between the DRadon-projections is used for camera zoom estimation. Combining the estimated motion parameters, an affine transformation is developed for inter-frame stabilization. Comparative performance using motion accuracy and frame stability is evaluated over different categories of real-world videos.
机译:本文提出了一种新的基于投影的仿射运动稳定器框架,用于使用差分拉顿(DRadon)曲线翘曲实现视频稳定。将基于经典投影的算法的平移域扩展到仿射稳定,最近已探究了用Radon或旋转图像获得的多个角度曲线,以进行组合的旋转和缩放估计。 on提供有效的投影提取,但是在局部变化下使用积分强度会降低所需的运动精度。 DRadon处理每个角度切片的导数,以合并基于形状的匹配以实现更好的投影对齐。基于人类对不稳定摄像机记录中的帧间倾斜的感知,建议的角度DRadon曲线估计被限制在[-20°,20°]的角度搜索空间中,角度增量为0.1°。从参考帧的完整角DRadon曲线集中,选择五个关键角切片并将其与目标DRadon中的相应邻域相关联,以进行帧间倾斜估计。使用新颖的多约束方法对参考和目标DRadon的最佳匹配关键片段进行扭曲,并对提取的扭曲向量进行进一步处理以进行平移和缩放估计。基于DRadon投影之间的相对拉伸/收缩的矢量斜率算法用于相机缩放估计。结合估计的运动参数,仿射变换被开发用于帧间稳定。在不同类别的真实视频中评估了使用运动精度和帧稳定性的比较性能。

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