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Rigid 3-D motion estimation using neural networks and initially estimated 2-D motion data

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3 Author(s)
Tzovaras, D. ; Inf. & Telematics Inst., Thessaloniki, Greece ; Ploskas, N. ; Strintizis, M.G.

This paper extends a known efficient technique for rigid three-dimensional (3-D) motion estimation so as to make it applicable to motion estimation problems occuring in image sequence coding applications. The known technique estimates 3-D motion using previously evaluated 3-D correspondence. However, in image sequence coding applications, 3-D correspondence is unknown and usually only two-dimensional (2-D) motion vectors are initially available. The novel neural network (NN) introduced in this paper uses initially estimated 2-D motion vectors to estimate 3-D rigid motion, and is therefore suitable for image sequence coding applications. Moreover, it is shown that the NN introduced in this paper performs extremely well even in cases where 3-D correspondence is known with accuracy. Experimental results are presented for the evaluation of the proposed scheme

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Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:10 ,  Issue: 1 )