Recovery of 3D Information from 3D Range Data and from 2D/3D Optical Flow and 3D Scene/Range Flow

通过2D/3D光流和3D场景/距离流计算运动是我长期的主要研究兴趣。我的另一个主要兴趣是应用这些和其他计算技术，以非侵入性、非接触的方式从3D范围数据测量3D植物生长。在接下来的5年里，我的主要短期主要研究目标是：*(1)在真实图像数据中测量准确的遮挡边界上的二维光流。当前的正则化方法产生的流往往会在遮挡边缘(两个不同移动对象的图像相遇的地方)之间发生“出血”。我们建议计算闭合分段区域内部的流动，以产生(正确地)在遮挡边界处突然变化的流动。*(2)测量立体和距离图像序列上的精确3D场景/范围流动(曲面上的3D光流)。这种类型的3D光流使用从立体图像(场景流)产生的深度图来测量场景可见部分的3D运动，或使用距离传感器直接测量。我们希望产生实时的场景/范围流，例如，将在汽车驾驶中有用。*(3)以非侵入性、非接触的方式从生长植物的3D范围数据测量3D定量植物生长。这将允许对植物在其整个生命周期中的生长进行定量评估。一种应用是量化野生型和转基因植物的生长速度。

The computation of motion via 2D/3D optical flow and 3D scene/range flow is my long term primary research interest. I have an additional primary interest in in applying these and other computational techniques to measure 3D plant growth from 3D range data in a non-invasive, non-contact manner. Over the next 5 years, my key short term primary research objectives are:***(1) To measure accurate 2D optical flow at occlusion boundaries in real image data. Currently regularization approaches produce flow that tends to "bleed" across occlusion edges (where the images of two differently moving objects meet). We propose to compute the flow inside of closed segmented regions to produce flow that (correctly) abruptly changes at occlusion boundaries.***(2) To measure accurate 3D scene/range flow (3D optical flow on surfaces) on stereo and range image sequences. This type of 3D optical flow measures the 3D motion of visible parts of a scene using depth maps produced from stereo images (scene flow) or directly measured using a range sensor. We hope to produce real time scene/range flow that would be useful in car driving, for example.***(3) To measure 3D quantitative plant growth from 3D range data of growing plants in a non-invasive, non-contact manner. This will allow the quantitative evaluation of a plant's growth over its life cycle. One application would be to quantify the growth rate of wild type and genetically modified plants.