Pi Robot's profile - activity

Hello,

I have used calcBackProject() with color histograms to successfully locate a target patch within an image. I was wondering if I can do something similar using gradient histograms instead of color? From the digits.py example I see how I can construct gradient histograms from Sobel edge filters. But is there a way I can now plug these into the calcBackProject() function to locate a target in an image?

Thanks!
patrick

OK thanks.

Thanks @berak for the reply. And yes, I am familiar with cross-validation methods. So it seems I don't understand the meaning of "confidence" as used with the FaceRecognizer. Are you saying that the meaning of "confidence" is the same as "distance"? This seems backwards to me. If the distance between the test image and itself is zero, shouldn't the confidence of the match be 100% (1.00)?

Hello,

I am trying the facerec_demo.py script on the AT&T face database and the confidence value returned for any image in the original training database is 0.00. Is that expected behavior?

Thanks!
patrick