A neural network based motion-estimation technique is developed, that is applicable to sub-pixel as well as large movements. Experiments on typical test frame sequences indicate marked improvement in accuracy of motion vector estimates over the MPEG logarithmic block matching algorithm. The method utilizes a modified Hopfield neural network. Due to the neural network's fault-tolerant nature and parallel computation capability, fast, accurate, and reliable results are obtained. Application to MPEG based video compression is also discussed.<>


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    Title :

    Neural network based motion vector computation and application to MPEG coding


    Contributors:


    Publication date :

    1994-01-01


    Size :

    496887 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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