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Visual object tracking in video can be formulated as a time varying appearance-based binary classification problem. Tracking algorithms need to adapt to changes in both foreground object appearance as well as varying scene backgrounds. Fusing information from multimodal features (views or representations) typically enhances classification performance without increasing classifier complexity when image...
Ensemble methods provide a principled framework for building high performance classifiers and representing many types of data. As a result, these methods can be useful for making inferences in many domains such as classification and multi-modal biometrics. We introduce a novel ensemble method for combining multiple representations (or views). The method is a multiple view generalization of AdaBoost...
A robust face watermarking scheme is proposed to provide a solution to copyright protection of semantic content. To address the issue of less robustness to geometric attacks in watermarking scheme, Zernike moments based invariant features are extracted and some selected Zernike moments are proposed to carry a multi-bit watermark. Watermark signal is embedded into face region in the intensity spatial...
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