For a performance measuring purpose I am trying to draw ROC curve. In ROC curve I have to plot False Positive Rate (FPR) in x-axis and True Positive Rate (TPR) in y-axis. As we know,
FPR = FP/(FP+TN)
So in the following picture how can i detect True Negative(TN) ? I have used HOG classifier to detect human. I marked with rectangle 1,2,3,4,5,6(or should be 7) to show the human objects that should be ignored and not to classify as human. and I think those are True Negative.
In this picture i want to say my assumption,as we know,
False negative: Result should have been positive, but is negative.
False positive: Result should have been negative, but is positive.
True positive: Result should have been positive and is positive.
True negative: Result should have been negative and is negative
So i think in this frame FP = 0, TP = 0, FN = 0 but not sure about TN, is it 6 or 7 or anything other? Please correct me also about FP, TP, and FN if i am wrong. I saw this question How to categorize True Negatives in sliding window object detection? which was really helpful but still i have to calculate FPR for this scenario.