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Using Haar-like feature classifiers for hand tracking in tabletop augmented reality

Abstract

We propose in this paper a hand interaction approach to Augmented Reality Tabletop applications. We detect the user’s hands using haar-like feature classifiers and correlate its positions with the fixed markers on the table. This gives the user the possibility to move, rotate and resize the virtual objects located over the table with their bare hands.Postprint (published version

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