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Motion detection and estimation for image sequence analysis using fan filtering and time-recursion method

机译:利用扇形滤波和时间递归方法进行图像序列分析的运动检测和估计

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Using the spatio-temporal characteristics and spectral properties of motion in the sequence of images a motion estimation algorithm for detecting and estimating the exact shapes and textures and instantaneous positions of moving objects is presented. The described motion analysis filter bank incorporating the motion-vector-selective fan filters with the time-recursive Kalman filter working in parallel has an ability of extracting the multiple moving objects embedded in the sequence of image frames of the cluttered stationary background. Simulations were performed to verify the claimed properties of our filter bank using real, natural terrain image sequences. The results have shown us a good performance of detecting and estimating each one of multiple moving objects that undergoes constant rate translation and rotation in both of noiseless and noisy image sequences.
机译:利用图像序列中运动的时空特性和光谱特性,提出了一种运动估计算法,用于检测和估计运动对象的精确形状和纹理以及瞬时位置。所描述的运动分析滤波器组结合了运动矢量选择性风扇滤波器和并行运行的时间递归卡尔曼滤波器,具有提取嵌入在混乱的固定背景图像帧序列中的多个运动对象的能力。使用真实,自然的地形图像序列进行了仿真,以验证我们所要求的滤光片组特性。结果显示了我们对检测和估计在无噪声和有噪声图像序列中经历恒定速率平移和旋转的多个运动对象中的每一个的良好性能。

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