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An adaptive system of velocity estimation for digital images

机译:数字图像速度估计的自适应系统

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The estimation of velocity has been proposed as a preprocessing step for many high-level vision algorithms for digital images. A new Galerkin inverse finite element approach is described for estimating velocity which uses an adaptive triangular mesh in which the resolution only increases where motion is found to occur. The mesh facilitates a reduction in computational effort by enabling processing to focus on particular objects of interest in a scene, specifically those areas where motion is detected without expending effort on computing flow for regions in which there is no motion. A confidence measure is calculated for the detected motion and if this measure passes a threshold then the motion is used for an adaptive mesh refinement process. The method is applied to real images where a significant part of the image is static. Results show that the adaptive framework estimates motion efficiently without loss of accuracy.
机译:已经提出了速度估计作为许多高级数字图像视觉算法的预处理步骤。描述了一种新的Galerkin逆有限元方法,该方法用于估计速度,该方法使用自适应三角形网格,其中分辨率仅在发现运动发生的地方才增加。网格通过使处理能够集中于场景中的特定感兴趣对象,特别是检测到运动的那些区域而无需花费精力来计算没有运动的区域的流量,从而有助于减少计算量。为检测到的运动计算置信度,如果该测量通过阈值,则将该运动用于自适应网格细化过程。该方法适用于图像的很大一部分是静态的真实图像。结果表明,自适应框架可以有效地估计运动,而不会降低准确性。

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