Bayesian tracking by discriminant feature fusion and evolutionary importance resampling

Abstract

Tracking success or failure depends heavily on how distinguishable the features separating the target object from its surroundings. From local image features, three likelihood ratio features are generated for measuring the confidence scores of pixels belonging to object or background category in this paper; and further are fused to classify them into object… (More)

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