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Hi, in my opinion you should count true negatives (TN) for each location where you apply your HoG classifier. Because, you can also get for each location where you apply your classifier a true positive (TP), false positive (FP) or a false negative (FN).
Typically you count the results to evaluate the classifier quality by building some statistics (Receiver Operating Characteristic, Detection rate vs. false positive, ...). This statistics should be independent from the image size. Dalal and Triggs compare their HoG detector with other algorithms in a DET curve (miss rate against false positive per window).
If you want to evaluate the quality of your system on image level you can plot the detection rate against the false positive per window. But this kind of statistic depends heavily on the size of the image.
