DocumentCode
3139476
Title
Robust estimation of a multi-layered motion representation
Author
Darrell, Trevor ; Pentland, Alex
Author_Institution
Media Lab., MIT, Cambridge, MA, USA
fYear
1991
fDate
7-9 Oct 1991
Firstpage
173
Lastpage
178
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
Keywords
image segmentation; image sequences; motion estimation; edge-based discontinuity model; estimation methods; layered model; minimal-covering optimization; model parameters; multi-layered motion representation; multiple moving objects; parallel robust estimation techniques; real image sequences; segmentation; transparent phenomena; Coherence; Computer vision; Humans; Image segmentation; Image sequences; Layout; Machine vision; Motion estimation; Robustness; Smoothing methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Visual Motion, 1991., Proceedings of the IEEE Workshop on
Conference_Location
Princeton, NJ
Print_ISBN
0-8186-2153-2
Type
conf
DOI
10.1109/WVM.1991.212810
Filename
212810
Link To Document