This paper presents a corner based voting method for estimating the object shift in video image frames. Information about the corners distribution around a reference point is used to represent the object shape and then to find the most probable target position in the next frame. Tracking is done through using a voting space obtained by matching corners information. A motion vector for the reference point is nonlinearly estimated with three different strategies by using the global information of the matched corners. The results show a comparison between three considered strategies for estimating the object shift.

"A COMPARISON OF DIFFERENT APPROACHES TO NONLINEAR SHIFT ESTIMATION FOR OBJECT TRACKING"

REGAZZONI, CARLO;
2007

Abstract

This paper presents a corner based voting method for estimating the object shift in video image frames. Information about the corners distribution around a reference point is used to represent the object shape and then to find the most probable target position in the next frame. Tracking is done through using a voting space obtained by matching corners information. A motion vector for the reference point is nonlinearly estimated with three different strategies by using the global information of the matched corners. The results show a comparison between three considered strategies for estimating the object shift.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/237591
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