MULTI-TARGET TRACKING IN NON-OVERLAPPING SURVEILLANCE CAMERAS USING PREDEFINED REFERENCE SET
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Abstract
In this paper, we consider multi-object target tracking using video reference datasets. Our objective is detection of the target using a novel adaboost and Gentle Boost method in order to track the subjects from reference data sets. Multi-target tracking is still challenging topic which is used to find the same object across different camera views and also used to find the location and sizes of different object at different places. Furthermore extensive performance analysis of the three main partsdemonstrates usefulness of multiobject tracking. We carried out experiment to analyze discriminative power of nine features (HSV, LBP, HOG extracted on body, torso and legs) used in the appearance model for multicam dataset. For each features the RMSE and PSNR obtained.
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