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Multistrategy Fusion
Using Mixture Model For Moving Object Detection
Presented by: Sohail Nadimi
ABSTRACT : In a video surveillance domain, mixture models
are used in conjunction with a variety of features and filters
to detect and track moving objects. However, these systems
do not provide clear performance results at the pixel detection
level. In this paper, we apply the mixture model to provide
several fusion strategies based on the competitive and cooperative
principles of integration which we call OR, and, AND strategies.
In addition, we apply the Dempster-Shafer method to mixture
models for object detection. Using two video databases, we
show the performance of each fusion strategy using receiver
operating characteristic (ROC) curves.
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