<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>

CC BY-SA 4.0
2020-01-22T13:32:50.053Z
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"?
nbro
CC BY-SA 4.0
2020-01-22T16:18:34.797Z
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)
Paltusok
CC BY-SA 4.0
2020-01-24T11:33:15.997Z
So you are talking about the Jaccard similarity?!
nbro
CC BY-SA 4.0
2020-02-19T14:48:31.333Z
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.
Neil Slater
<neural-networks><machine-learning><object-detection>
What is the expected value of an IOU in this case?
Paltusok
# 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.  

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## 0 answers

