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# System prepended metadata

title: Feature idees kevin

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# Feature idees kevin

Issue

Often confused with c.OOK, why?
c.OOK: ZELFDE-A is just twice the movement of c.OOK. Averaged over two parts of sequence might look the same
When hands move close together, hand tracking fails

solution:
Count how many times two wijsvingers touch eachother 
but first check how good hands are tracked at the  moment both touche:



To better differentiate between signs that  use two hands that touch  eachoter or  signs where  one hand  remains still and not near the  other hand, maybe calculate min  distance between both hands, bare in mind we dont use undetected keypoints


Maybe  check how much a hand has moved across the frames to detect if it is a dominant hand , could also  be used to detect if he uses both hands, so sum of distances of hand between al frames





![](https://i.imgur.com/sk92Wzh.png)
![](https://i.imgur.com/KYjORwe.png)
when we take the distances between both ring fingers, of a interpolated sequence of 4 with preprocessing, we can see that most classes are hard to  differentiate and have outliers




![](https://i.imgur.com/DlkkHTQ.png)
doing min max 

![](https://i.imgur.com/vE3p4zd.png)
I took 0.1 distances as being close together the ring  fingers, I then took the amount end average=#/len(sequence)
We can see  that (2)  3 and 7 are almost never  togehter  except  some outliers.  


![](https://i.imgur.com/LqVxUOF.png)
if we look at the confusion matrix, we can see  that c ook and zelfde A are better differentiable, probably because we now have more temporal data



if we use only the temporal count and avg count
![](https://i.imgur.com/Tzs0zsJ.png)

we can see that min and max did a decent  job, count improved overal  score but  not in  the  2 focused classes




