Robust estimation of a multi-layered motion representation

A layered model of scene segmentation based on explicitly representing the support of a homogeneous region is introduced, which employs parallel robust estimation techniques, and uses a minimal-covering optimization to estimate the number of objects in the scene.

Abstract

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. Traditional approaches to this problem rely on an edge-based discontinuity model, and have problems with transparent phenomena. The authors introduce a layered model of scene segmentation based on explicitly representing the support of a homogeneous region. The 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, they successfully segment real image sequences containing multiple motions.>