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Pyramidal Markov random field (MRF) models for optical flow estimation a

机译:用于光流估计的金字塔形马尔可夫随机场(MRF)模型

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Abstract: In air-to-ground applications, the detection of target is a difficult problem due to complex background where classical detection algorithms generate a large amount of false alarms. This paper addresses the detection of moving target based on motion compensated sequences. In the presence of noisy image acquisition and motion discontinuities, the estimation of optical flow is reformulated in robust estimation framework. The motion estimation is based on robust optical flow algorithm developed in the pyramidal Markov Random Model framework. We present the results of this detection algorithm on real-world airborne I.R. image sequence.!7
机译:摘要:在空对地应用中,由于背景复杂,传统的检测算法会生成大量的虚假警报,因此目标的检测是一个难题。本文讨论了基于运动补偿序列的运动目标检测。在存在嘈杂的图像采集和运动不连续性的情况下,光流的估计将在鲁棒估计框架中重新制定。运动估计基于在金字塔马尔可夫随机模型框架中开发的鲁棒光流算法。我们在实际的机载I.R.上展示了这种检测算法的结果。图像序列!! 7

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