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Abstract:

This paper proposes a new method for recovering nonrigid motion and structure of clouds under affine constraints using time-varying cloud images obtained from meteorological satellites. This problem is challenging not only due to the correspondence problem but also due to the lack of depth cues in the 2D cloud images (scaled orthographic projection). In this paper, affine motion is chosen as a suitable model for small local cloud motion. However, the cloud motion model can also be extended and not necessarily be affine. Analysis of intensity images is first used to find the candidates of correspondence for each point. Then affine motion model is utilized to find the structure (cloud-top height), motion parameters, and point correspondences. Extensive analysis has been done on defining appropriate constraints on depth that are necessary for achieving converge. Finally, experimental results on time-varying images of hurricane Luis, captured by GOES-9 satellite in geosynchronous orbit are presented. We believe that this is the first reported work on estimating structure and motion under scaled orthographic views, when the object of interest is undergoing a nonrigid motion. Our results are very encouraging, and have many potential applications especially in earth and space sciences.

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