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Pointing Out Examples of Colors

The complete process required for pointing out an object (or a blob) of a named color in one's field of view is schematized in Figure .

Compared to the color naming process, we also need a pointing device (a color monitor is suggested in the diagram, but other pointing devices like a robot arm could be used), a complete color image (frame) rather than just a blob, and an index into the image for each blob to be categorized. In Chapter , I present an application along these lines, and further implementation detail is provided there.

When given a color name to point out an example referent of, we sample the image using a certain sample (blob) size, collecting the averaged device RGB values and the image coordinates of (the center of) each blob, and transform the RGB values to the color space of choice, which gives us a set of points in color space with corresponding image coordinates:

where is a point in color space, is the position vector of the corresponding (center of the) blob in the image (field of view), and is the total number of samples (blobs).

We then determine the membership (goodness) value of the samples in the appropriate category:

where is the normalized Gaussian as before, and is the category with which the name is associated, with its corresponding parameters and .

Next we select all samples with a membership value exceeding the threshold for category membership :

These are all candidate referents for the name N.

As before, we sort the candidates by decreasing membership value:

If we just want any referent for the category named N, we pick an arbitrary element from this tuple (or from set B), and if we want the best example we take the first element .

After selecting a referent , all that is left to do is point it out in the image (or in the world giving rise to the image, which is harder to do), using the index vector .

As is the case with color naming, we can do forced choice experiments if we use a zero threshold, in which case a referent will always be selected regardless of how good an example it is, or we can do free choice experiments using the standard threshold , in which case a referent will only be selected if it is a ``good enough'' example of the category in question.