Thursday, November 17, 2016

Creating Our Negative Samples + Negative Description File

When researching different ways to develop negative samples, we found that we obtain the best results for the classifier by having a slight variant of the features we wish to detect embedded in an image that does not contain any characteristics of the image.
Negative images can be anything, but the classifier is more accurate if it includes a variant of a positive sample. Ideally negative images would look exactly like the positive samples, except they wouldn't contain the object we want to recognize.

 Using Gimp, an image manipulation program we placed images of ears in the foreground of a background/backdrop.

Examples of Negative Samples:

Negative Description File:

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