In this paper we address the problem of visual surveillance, which we define as the problem of optimally extracting information from the visual scene with a fixating, foveated imaging system. We are explicitly concerned with eye/camera movement strategies that result in maximizing information extraction from the visual field. Here we demonstrate how a novel characterization of the contrast statistics of natural images can be used for selecting fixation points that minimize the total contrast uncertainty (entropy) of natural images. We demonstrate the performance of the algorithm and compare its performance to ground truth methods. The results show that our algorithm performs favorably in terms of both efficiency and its ability to find salient features in the image.


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    Title :

    Natural contrast statistics and the selection of visual fixations


    Contributors:
    Raj, R.G. (author) / Geisler, W.S. (author) / Frazor, R.A. (author) / Bovik, A.C. (author)


    Publication date :

    2005-01-01


    Size :

    325379 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Natural Contrast Statistics and the Selection of Visual Fixations

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