Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Motion segmentation using occlusions Abhijit S. Ogale, Cornelia Fermller, Yiannis Aloimonos
 

Summary: 1
Motion segmentation using occlusions
Abhijit S. Ogale, Cornelia Fermüller, Yiannis Aloimonos
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).

  

Source: Aloimonos, Yiannis - Center for Automation Research & Department of Computer Science, University of Maryland at College Park
Fermüller, Cornelia - Center for Automation Research, University of Maryland at College Park

 

Collections: Computer Technologies and Information Sciences; Engineering