从移动平台拍摄的湍流影像中分离出物体运动的光流，提升目标检测精度。
Investigation of moving objects through atmospheric turbulence from a non-stationary platform
- 先建模并补偿相机运动引起的光流，再分离湍流与物体运动
- 通过时空分解方法有效分离湍流干扰与真实物体运动光流
- 适用于无人机、车载等动态平台的视觉感知系统
本文从移动相机拍摄的受大气湍流影响的图像序列中，提取移动物体对应的光流场。首先计算光流并建立运动模型以补偿由相机运动引起的光流；随后将该运动补偿后的光流场输入到我们先前的工作（Gilles et al. — 2018）中，采用基于时空卡通+纹理的分解方法，分离出大气湍流和物体运动所导致的光流成分。最后，对几何成分使用检测与跟踪方法处理，并与真实轨迹对比验证。本研究所用的所有序列与代码均已开源，可向作者索取。
原文摘要 · Abstract (English)
In this work, we extract the optical flow field corresponding to moving objects from an image sequence of a scene impacted by atmospheric turbulence \emph{and} captured from a moving camera. Our procedure first computes the optical flow field and creates a motion model to compensate for the flow field induced by camera motion. After subtracting the motion model from the optical flow, we proceed with our previous work, Gilles et al~\cite{gilles2018detection}, where a spatial-temporal cartoon+texture inspired decomposition is performed on the motion-compensated flow field in order to separate flows corresponding to atmospheric turbulence and object motion. Finally, the geometric component is processed with the detection and tracking method and is compared against a ground truth. All of the sequences and code used in this work are open source and are available by contacting the authors.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。