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I am reading this paper in an attempt to recreate the salient region detection and segmentation model employed. I have the following questions pertaining to section 3 of the paper and I would highly appreciate it if someone could provide clarity on them.

  1. The word "scales" is used at multiple points in the section, for example, line 4 of the section states "saliency maps are created at different scales". I do not exactly understand what the authors mean by the word scales. Moreover, is there a mathematical way to think about it?

  2. I understand that a saliency value enter image description here is computed for each pixel at (enter image description here) using the equation enter image description here

However, there is no mention of enter image description here in the equation. Hence, I am confused as to what pixel the saliency value is being computed for. Is it enter image description here?

  1. I did not understand what the authors meant by the term "bin" in section 3.2 line 5 where it is stated, "The hill-climbing algorithm can be seen as a search window being run across the space of the d-dimensional histogram to find the largest bin within that window."

Lastly, any other tips or clarifications are most welcome and much appreciated!

  • In case you are unable to access the link to the research paper, the following citation may help: Achanta, R., Estrada, F., Wils, P., & Süsstrunk, S. (2008, May). Salient region detection and segmentation. –  Jul 17 '21 at 08:15
  • I’m voting to close this question because it is not about programming. Possibly belongs on https://math.stackexchange.com/, if on topic there. – niton Jul 18 '21 at 02:36
  • The questions here have already been answered [here](https://ai.stackexchange.com/q/28740/2444), so I guess this post should be closed. – nbro Oct 11 '21 at 10:02
  • I’m voting to close this question because it has already an answer on another site and it's off-topic here. – nbro Oct 11 '21 at 10:03

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