11. A computer-implemented method as in claim 10 , wherein: the one or more goals comprise creation of positive example images that cause the classifier to indicate non-appearance of the predetermined emotion, affective state, or action unit, and the example images appear as expression of the predetermined emotion, affective state, or action unit; and the objectively qualified images that do not pass the first quality check are not sent to the one or more experts; the method further comprising: training the classifier using the one or more images that passed the second quality check as positive examples of appearance of the predetermined emotion, affective state, or action unit; and using the classifier after the step of training.
11. A computer-implemented method as in claim 10 , wherein: the one or more goals comprise creation of positive example images that cause the classifier to indicate non-appearance of the predetermined emotion, affective state, or action unit, and the example images appear as expression of the predetermined emotion, affective state, or action unit; and the objectively qualified images that do not pass the first quality check are not sent to the one or more experts; the method further comprising: training the classifier using the one or more images that passed the second quality check as positive examples of appearance of the predetermined emotion, affective state, or action unit; and using the classifier after the step of training. 12. A computer-implemented method as in claim 11 , wherein the steps of providing one or more goals, receiving from the first plurality of untrained providers images created in response to the step of providing one or more goals, sending to a second plurality of untrained providers requests to rate, and receiving ratings of the second plurality of untrained providers are performed by a computer-based system over a network coupling the computer-based system to provider machines of the providers of the first and second pluralities of untrained providers.