In this paper, we study the tracking of deformable shapes in sequences of images. Our target application is the tracking of clouds in satellite images. We propose to use a recent state-of-the-art method for off-the-grid sparse analysis to describe clouds in image as mixtures of 2D atoms. Then, we introduce a method to handle the tracking with its specificities: apparition or disappearance of objects, merging, and splitting. Numerically, this method corroborates the magnitude of the results provided by recent state-of-the-art alternatives. Unlike its counterparts, the choice or regularization and correlation parameters allows additional flexibility regarding the interpretation of clouds’ life cycles. Finally, it also provides additional information on the cloud temperature during its life cycle, which seem in accordance with the underlying physical processes.

在本文中，我们研究了图像序列中可变形形状的跟踪。我们的目标应用是跟踪卫星图像中的云。我们建议使用最新的方法进行网格稀疏分析，以将图像中的云描述为2D原子的混合物。然后，我们介绍一种处理跟踪的方法，它具有以下特殊性：对象的消失或消失，合并和拆分。从数字上讲，这种方法证实了最新的替代技术所提供的结果的重要性。与同类产品不同，选择或正则化和相关性参数在解释云的生命周期方面提供了更多的灵活性。最后，它还提供了有关其生命周期中云温度的其他信息，