Multilayer robust estimation for motion segmentation

In order to recover an accurate representation of a scene containing multiple moving objects, one must use estimation methods that can recover both model parameters and segmentation at the same time. We introduce a new layered model of scene segmentation based on explicitly representing the support of a homogeneous region. Our model employs parallel robust estimation techniques, and uses a minimal-covering optimization to estimate the number of objects in the scene. Using a simple direct motion model of translating objects, we successfully segment real image sequences containing multiple motions.

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