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Motion estimation of deformable target over infrared camera video in coarse resolution with possible frame-out of target by particle filter

机译:粗略分辨率的红外摄像机视频上可变形目标的运动估计,并可能通过粒子滤波器对目标进行画框

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Motion estimation of deformable target over infrared camera video in coarse resolution with possible frame-out of the target by an elaborated particle filter has been proposed. Target state consists of location factor and shape factor of the target, where the location factor is position of the center of gravity of the target over the image plane, and the shape factor is a set of connected pixels that forms appearance of the target over the image plane. The location factor is formulated in real number space, while the shape factor is formulated in pixel based manner. State space model has been formed by a system model to represent a smooth motion of the target and smooth change of its shape, and by an observation model to evaluated likeliness of the state based on an appearance of the target over the image plane. We have employed a mixture model for the location factor of the system model consisting of second order difference equation for smooth change and uniform distribution over the image plane to cope with abrupt change of the location due to lack of frame rate in the video. For the smooth change of the target shape, we propose to use a Markov Chain Monte Carlo move on the set of connected pixels. Experiments on some real video images explore the performance of the proposed method through a prototyped implementation by simplifying the method with rough approximation of the target shape with a rectangle.
机译:提出了在红外摄像机视频上以粗糙分辨率对可变形目标进行运动估计的方法,其中可能通过精心设计的粒子滤波器对目标进行画框。目标状态由目标的位置因子和形状因子组成,其中位置因子是目标的重心在图像平面上的位置,形状因子是一组连接的像素,它们形成目标在图像上的外观。图像平面。位置因子是在实数空间中制定的,而形状因子是基于像素的方式制定的。状态空间模型由系统模型(表示对象的平滑运动和对象形状的平滑变化)以及观察模型(基于对象在图像平面上的外观)评估状态的相似性组成。我们对系统模型的位置因子采用了混合模型,该模型由二阶差分方程组成,用于平滑变化和在图像平面上均匀分布,以应对由于视频中缺少帧频而导致的位置突然变化。为了使目标形状平滑变化,我们建议在连接的像素集上使用马尔可夫链蒙特卡罗移动。在一些真实的视频图像上进行的实验通过原型实现方式,通过用矩形大致逼近目标形状来简化该方法,从而探索了该方法的性能。

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