Location-based context is important for many applications. Previous systems offered only coarse room-level features or used manually specified room regions to determine fine-scale features. We propose a location context mechanism based on activity maps, which define regions of similar context based on observations of 3-D patterns of location and motion in an environment. We describe an algorithm for obtaining activity maps using the spatio-temporal clustering of visual tracking data. We show how the recovered maps correspond to regions for common tasks in the environment and describe their use in some applications.


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    Title :

    Activity maps for location-aware computing


    Contributors:
    Demirdjian, D. (author) / Tollmar, K. (author) / Koile, K. (author) / Checka, N. (author) / Darrell, T. (author)


    Publication date :

    2002-01-01


    Size :

    348047 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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