Motion segmentation using occlusions

Citations Over TimeTop 10% of 2005 papers

Abstract

We examine the key role of occlusions in finding independently moving objects instantaneously in a video obtained by a moving camera with a restricted field of view. In this problem, the image motion is caused by the combined effect of camera motion (egomotion), structure (depth), and the independent motion of scene entities. For a camera with a restricted field of view undergoing a small motion between frames, there exists, in general, a set of 3D camera motions compatible with the observed flow field even if only a small amount of noise is present, leading to ambiguous 3D motion estimates. If separable sets of solutions exist, motion-based clustering can detect one category of moving objects. Even if a single inseparable set of solutions is found, we show that occlusion information can be used to find ordinal depth, which is critical in identifying a new class of moving objects. In order to find ordinal depth, occlusions must not only be known, but they must also be filled (grouped) with optical flow from neighboring regions. We present a novel algorithm for filling occlusions and deducing ordinal depth under general circumstances. Finally, we describe another category of moving objects which is detected using cardinal comparisons between structure from motion and structure estimates from another source (e.g., stereo).

Related Papers

• A New Method of 3D Motion and Structure Estimation Based on Spare Optical Flow(2003)
• → Effective Motion Field Description Based On Affine Models And Global Motion Information(1996)2 cited
• → <title>Motion restoration: a method for object and global motion estimation</title>(1994)1 cited
• → Parameter Estimation Of Non - Translational Motion Fields(1996)
• → Block/object-based algorithm for estimating true motion fields(2000)