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 :
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