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Video motion estimation using a neural network

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2 Author(s)
Skrzypkowiak, S.S. ; Dept. of Electr. Eng., Univ. of South Florida, Tampa, FL, USA ; Jain, V.K.

This paper presents a novel technique for motion estimation in video frame sequences. It uses a modified Hopfield neural network. The procedure consists of two stages: estimation of the neural network parameters from the present and past frames or subimages, followed by estimation of the motion vector. The latter utilizes a dynamic iterative algorithm to minimize the energy function of the neural network. Due to the neural network's fault-tolerant nature and parallel computation capability, fast, accurate, and reliable results are obtained. The usefulness and accuracy of the approach is demonstrated upon both synthetic and real images

Published in:

Circuits and Systems, 1994. ISCAS '94., 1994 IEEE International Symposium on  (Volume:3 )

Date of Conference:

30 May-2 Jun 1994