Abstract:
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In this paper we present a new system for segmenting non-rigid objects in moving camera sequences for indoor and outdoor sce
narios that achieves a correct object segmentation via global MAP-MRF
framework formulation for the foreground and background classification
task. Our proposal, suitable for video indexation applications, receives
as an input an initial segmentation of the object to segment and it consists of two region-based parametric probabilistic models to model the
spatial (x,y) and color (r,g,b) domains of the foreground and background
classes. Both classes rival each other in modeling the regions that appear
within a dynamic region of interest that includes the foreground object
to segment and also, the background regions that surrounds the object.
The results presented in the paper show the correctness of the object
segmentation, reducing false positive and false negative detections originated by the new background regions that appear near the region of the
object |