Body: <p>I have a detection problem. An object with a probability of 0.5 is in a box with coordinates ((0,0), (2, 2)) and with a probability of 0.5 a box with coordinates ((2,0), (4,2)). </p>
  
  <p>What is the maximum expected value of an <a href="https://en.wikipedia.org/wiki/Jaccard_index" rel="nofollow noreferrer">intersection over union (IOU)</a> with an object that a constant detection algorithm that produces one box can reach? I can't understand how I should find the expected value here. P.S. IOU is 0 cos intersection is empty.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-01-22T13:32:50.053Z
Comments.Text: Hi and welcome to Artificial Intelligence SE! To clarify (given that I am not familiar with this abbreviation), what do you mean by "IOU"? Is it an abbreviation for "Intersection over Union"?
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-01-22T16:18:34.797Z
Comments.Text: Yes it is short form of "intersection over Union" . I was given this on the interview and still dont know what I should start with to do this)
Comments.UserDisplayName: Paltusok
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-01-24T11:33:15.997Z
Comments.Text: So you are talking about the Jaccard similarity?!
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-19T14:48:31.333Z
Comments.Text: Could you please give more details about what you mean by the object's probability of appearing in one box or another? I would take it to mean that you have a *low level* detection algorithm that is giving you these probabilities, and you want your higher level display algorithm to display a box with maximum IoU given that detection (in which case max IoU here is 0.5 because the boxes combine nicely to make a single box without gaps)? However, your first part of text does not mention any detector, just probability of an object appearing - in which case theoretical maximum IoU would be 1.0.
Comments.UserDisplayName: Neil Slater
Tags: <neural-networks><machine-learning><object-detection>
Title: What is the expected value of an IOU in this case?
UserDisplayName: Paltusok
ThreadText: # What is the expected value of an IOU in this case?
  
  (Asked by: username_0 on 2020-01-22)
  
  I have a detection problem. An object with a probability of 0.5 is in a box with coordinates ((0,0), (2, 2)) and with a probability of 0.5 a box with coordinates ((2,0), (4,2)).
  
  What is the maximum expected value of an [intersection over union (IOU)](https://en.wikipedia.org/wiki/Jaccard_index) with an object that a constant detection algorithm that produces one box can reach? I can't understand how I should find the expected value here. P.S. IOU is 0 cos intersection is empty.
  
  **Tags:** neural-networks, machine-learning, object-detection
  > **Comments:**
  > **username_1**: Hi and welcome to Artificial Intelligence SE! To clarify (given that I am not familiar with this abbreviation), what do you mean by "IOU"? Is it an abbreviation for "Intersection over Union"?  
  > **username_0**: Yes it is short form of "intersection over Union" . I was given this on the interview and still dont know what I should start with to do this)  
  > **username_1**: So you are talking about the Jaccard similarity?!  
  > **username_2**: Could you please give more details about what you mean by the object's probability of appearing in one box or another? I would take it to mean that you have a *low level* detection algorithm that is giving you these probabilities, and you want your higher level display algorithm to display a box with maximum IoU given that detection (in which case max IoU here is 0.5 because the boxes combine nicely to make a single box without gaps)? However, your first part of text does not mention any detector, just probability of an object appearing - in which case theoretical maximum IoU would be 1.0.  
  
  ---
  
  ## 0 answers
  
  