Thermal sensors bring a lot of benefits for object tracking due to the robustness to lighting changes over time, which still give a great difficulty to traditional tracking methods. Despite this powerful advantage, the ambiguity due to background clutters and occlusions makes the problem of thermal sensor-based tracking intractable. In this paper, we propose a novel framework for multiple object tracking in livestock breeding spaces using a single thermal sensor. The key idea of the proposed method is to define a new rotatable elliptical motion model, which is suitable for describing complicated motions of animals. Moreover, the proposed local constraint guides our tracker to robustly chase targets even with severe occlusions. Experimental results on various thermal video sequences show the significant improvement for tracking animals compared to other approaches proposed in the literature.

中文翻译：

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基于可旋转椭圆运动模型的自上而下热跟踪用于智能畜牧业

由于对光照随时间变化的鲁棒性，热传感器为物体跟踪带来了很多好处，这仍然给传统的跟踪方法带来了很大的困难。尽管有这个强大的优势，但由于背景杂乱和遮挡导致的模糊性使得基于热传感器的跟踪问题变得棘手。在本文中，我们提出了一种使用单个热传感器在牲畜饲养空间中进行多目标跟踪的新框架。该方法的关键思想是定义一个新的可旋转椭圆运动模型，适用于描述动物的复杂运动。此外，提出的局部约束指导我们的跟踪器即使在严重遮挡的情况下也能稳健地追逐目标。