A unified approach to moving object detection in 2D and 3D scenes

Abstract

The detection of moving objects is important in many tasks. Previous approaches to this problem can be broadly divided into two classes: 2D algorithms which apply when the scene can be approximated by a flat surface and/or when the camera is only undergoing rotations and zooms; and 3D algorithms which work well only when significant depth variations are present in the scene and the camera is translating. In this paper, we describe a unified approach to handling moving object detection in both 2D and 3D scenes, with a strategy to gracefully bridge the gap between those two extremes. Our approach is based on a stratification of the moving object detection problem into scenarios and corresponding techniques which gradually increase in their complexity. Moreover, the computations required for the solution to the problem at one complexity level become the initial processing step for the solution at the next complexity level.