deletions | additions       diff --git a/section_Reviewer_Comments_for_Authors__.tex b/section_Reviewer_Comments_for_Authors__.tex  index 7ea7e01..675bd19 100644  --- a/section_Reviewer_Comments_for_Authors__.tex  +++ b/section_Reviewer_Comments_for_Authors__.tex 
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\textit{That's exactly it! The False Positive class is indeed an extra set of training samples to allow the classifier to have a trained class of false positives. The benefit comes from allowing the use of a 'pre-trained-off-the-shelf' pedestrian detector. The user may not have access to re-training the pedestrian detector, but will for sure be able to include given samples (false positive samples) under a new class in the gallery of the re-identification algorithm.}  \textit{To drive this point home with the readers we've enriched the first paragraph of section 3.2 False Positives Class thusly:}  \textbf{\textit{Pedestrian detector algorithms usually produce some false positive detections. One way to improve their performance in a given context is to retrain the detector adding the false positives to the training as hard negatives on that specific context. However, some false positives may still remain, or the user may wish to use a 'pre-trained-off-the-shelf' PD algorithm where retraining is not an option.}}} option.}}  \textbf{\textit{Therefore,}}  \textbf{\textit{another contribution of our work is to adapt the RE-ID module to deal with the FP produced by the PD.}}