Automatic target recognition (ATR) algorithms have offered the promise of recognizing items of military importance over the past 20 years. It is the experience of the authors that greater ATR success would be possible if the ATR were used to "aid" the human operator instead of automatically "direct" the operator. ATRs have failed not due to their probability of detection versus false alarm rate, but to neglect of the human component. ATRs are designed to improve overall throughput by relieving the human operator of the need to perform repetitive tasks like scanning vast quantities of imagery for possible targets. ATRs are typically inserted prior to the operator and provide cues, which are then accepted or rejected. From our experience at three field exercises and a current operational deployment to the Bosnian theater, this is not the best way to get total system performance. The human operator makes decisions based on learning, history of past events, and surrounding contextual information. Loss of these factors by providing imagery, latent with symbolic cues on top of the original imagery, actually increases the workload of the operator. This paper covers the lessons learned from the field demonstrations and the operational deployment.


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    Title :

    Aided versus automatic target recognition


    Contributors:
    O'Hair, M. (author) / Purvis, B. (author) / Brown, J. (author)


    Publication date :

    1997


    Size :

    10 Seiten, 3 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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