deletions | additions       diff --git a/begin_quote_3_I_think__.tex b/begin_quote_3_I_think__.tex  index fedecac..ef19f22 100644  --- a/begin_quote_3_I_think__.tex  +++ b/begin_quote_3_I_think__.tex 
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\begin{quote}  3. I think the Window-based Classifier is exactly multi-shot. Some other multi-shot methods also do not require contiguous frames and in-camera trackers. The proposed Window-based Classifier is straightforward and reasonable. As an important contribution, it's better to compare it with other other multi-shot methods, such as reference [4].  \end{quote}  \textit{We thank the reviewer to point this out, as it suggests that we must the need to  clarify in the text that multi-shot algorithms that we are aware of (such as [4]) require a way to specify which images belong to a single person (such as a tracker or manual selection) prior to being able to analyze those images in a multi-shot fashion. No multi-shot algorithm that we are aware of does some kind of unsupervised clustering first to try and discover which images belong to a same individual, to then be able to use such data in a multi-shot fashion without a tracker or human intervention. Therefore, we have enhanced the clarifying paragraph thusly:}  \textbf{\textit{Although this procedure is similar to multi-shot, it requires less information. In this work, window-based classification works with any single-shot re-identification algorithm, and does not require an in-camera tracker or manual selection of the images that belong to each individual, contrary to all of the works that do multi-shot re-identification known to the authors.}}