5 ms·

I'm somewhat surprised at the responses for this. I believe your issue can be easily solved - have supervisors wear a distinctive color from a non-supervisor.

I'm somewhat surprised at the responses for this. I believe your issue can be easily solved - have supervisors wear a distinctive color from a non-supervisor. For example let's say it's yellow. OK so now you have yellow wearing supervisors and everyone else. To resolve the issue you have described acquire a month or so of footage, with labels per minute describing how many yellow wearing supervisors and how many people (in total) there are. So the data you have is: 1. Yellow wearing supervisors 2. Total amount of workers on the floor Then with this data you can train a network to do what you're describing pretty easily. Assuming there are a lot of workers on the floor, trying to do person detection or face detection would require too much data. Just have a uniform enforced and train on the colors/presence.

fareesh 7y ago
Sorry but it was a scenario I imagined and not something that happened in reality. I can't talk about some of the real-world scenarios that I am asked to consult on, so I made up a rather poorly thought-out one.
- jrumbut 7y ago
  Something to look at is the classic image processing algorithms that can be effective and more importantly behave predictably. In your example, take a film of the factory floor when it is empty, then once work begins use a approximately human sized/shaped rectangular sliding window and look for areas that exceed a threshold of difference to the image of the empty floor. You can then use that window as input to a classifier which will be easier due to the considerable dimension reduction or perhaps you can get sufficient performance using further deterministic techniques.
  - fareesh 7y ago
    Interesting approach, is this documented in a blog post or tutorial somewhere where something similar is done?
mrspeaker 7y ago
"Easily solved - just have them wear special clothes." Everything is easy if you can arbitrarily change the requirements!
- newfeatureok 7y ago
  The requirements were not changed. Supervisors of almost every working class position already wear different clothes to begin with. Heck, even doctors wear different clothing than nurses, teachers than students, coaches from athletes, etc. The general point is to capitalize on preexisting information than to do the "true" solution which is error prone and even a human might not have 100% accuracy at, due to the fact that in certain settings (such as this hypothetical) the perfected solution cannot be accomplished without constraints.
  - deleted 7y ago
    [deleted]
  - mrspeaker 7y ago
    This solution would change the work place culture - and I 100% bet would lead to a lot of good (for MY definition of good!) supervisors leaving. Imagine where you worked suddenly introduced this: "Yes, previously everyone could wear whatever they wanted - but from today, just the senior programmers must code while wearing a high-vis jacket around the office so we can track when they at their desks". The supervisors have now changed their relationship with coworkers - signaling their superiority, while simulataneously feeling stalked by their bosses, and looking "unfashionable"/un-cool - all because someone couldn't figure out how to do deep learning properly... which was the OP was actually asking about!
    - newfeatureok 7y ago
      I really don't understand your comment. 1. Supervisors are already by definition "superior" than their subordinates. 2. Supervisors on factories already wear distinctive clothing - especially in fully automated factories. Finally, you have yet to propose a solution to the problem yourself that would be highly accurate and easy to train. You vastly underestimate the difficulty to create a bespoke solution from scratch and no data. In any case since the supervisor thing was just an example - the original poster's only real choice is to manually label everything, but AI is really problem centric so it's hard to recommend anything without knowing the actual problem. Assuming it really is just [someone in an area for a period of time] kind of problem, and the difficulty is picking apart the 'someone' and you cannot influence their behavior, you just need massive amounts of data. Even then there's no guarantee you'll have high accuracy. If high accuracy is required the problem itself needs to be examined on a higher level.
SubiculumCode 7y ago
This is not bad, but once in this territory, why not just add some tracking beacon to a badge?
- newfeatureok 7y ago
  That is also a good idea. It really depends on what the rest of the requirements are.
Gatsky 7y ago
Reminds me of this: https://userweb.cs.txstate.edu/~br02/cs1428/ShortStoryForEngineers.htm https://userweb.cs.txstate.edu/~br02/cs1428/ShortStoryForEng...
deepGem 7y ago
This is a pragmatic and valid approach. No matter what anyone else says. Imagine, you told a 10 YO child to do this task. Even the child would ask the same question - how do I know who is a supervisor and who is not. Not only is face recognition hard, it is almost impossible to accomplish in a factory floor like setting. Not totally impossible but it is really really hard. Face detection is still possible but face recognition is far more computationally expensive. You'll need a shit ton of data and you'll need access to the employee database. You'll need a whole new engineering pipeline to make this happen and of course a team. Compared to that expense and time, you are way better off getting the company to approve special vests for supes.
- coredog64 7y ago
  I remember hearing a similar story circa 2003-2008. Some BigCo was spending a bunch of money to automate their inter office mail and was hung up on OCR of handwritten stuff. Some consultants come in to look and one asks if they can just use different color envelopes/baskets. The answer was “yes”.
asiachick 7y ago
Just passing on info but ANA (the airline company) has colored helmets in their maintenance to facility to distinguish supervisors (color 1) from non supervisors (color 2) and 1st year employees (colors 3) and guests (color 4). I don't know if they do any tracking.
- fareesh 7y ago
  This example was totally made-up. In my experience related to the type of arrangement you're describing - in reality (at least anecdotally speaking) the helmets are often not worn, or the colors are not enforced, or the colors don't get picked up due to poor quality video. I deal mostly with third-world countries so safety standards are not always the best.

fareesh 7y ago

Sorry but it was a scenario I imagined and not something that happened in reality. I can't talk about some of the real-world scenarios that I am asked to consult on, so I made up a rather poorly thought-out one.

jrumbut 7y ago
Something to look at is the classic image processing algorithms that can be effective and more importantly behave predictably. In your example, take a film of the factory floor when it is empty, then once work begins use a approximately human sized/shaped rectangular sliding window and look for areas that exceed a threshold of difference to the image of the empty floor. You can then use that window as input to a classifier which will be easier due to the considerable dimension reduction or perhaps you can get sufficient performance using further deterministic techniques.
- fareesh 7y ago
  Interesting approach, is this documented in a blog post or tutorial somewhere where something similar is done?

mrspeaker 7y ago

"Easily solved - just have them wear special clothes." Everything is easy if you can arbitrarily change the requirements!

newfeatureok 7y ago
The requirements were not changed. Supervisors of almost every working class position already wear different clothes to begin with. Heck, even doctors wear different clothing than nurses, teachers than students, coaches from athletes, etc. The general point is to capitalize on preexisting information than to do the "true" solution which is error prone and even a human might not have 100% accuracy at, due to the fact that in certain settings (such as this hypothetical) the perfected solution cannot be accomplished without constraints.
- deleted 7y ago
  [deleted]
- mrspeaker 7y ago
  This solution would change the work place culture - and I 100% bet would lead to a lot of good (for MY definition of good!) supervisors leaving. Imagine where you worked suddenly introduced this: "Yes, previously everyone could wear whatever they wanted - but from today, just the senior programmers must code while wearing a high-vis jacket around the office so we can track when they at their desks". The supervisors have now changed their relationship with coworkers - signaling their superiority, while simulataneously feeling stalked by their bosses, and looking "unfashionable"/un-cool - all because someone couldn't figure out how to do deep learning properly... which was the OP was actually asking about!
  - newfeatureok 7y ago
    I really don't understand your comment. 1. Supervisors are already by definition "superior" than their subordinates. 2. Supervisors on factories already wear distinctive clothing - especially in fully automated factories. Finally, you have yet to propose a solution to the problem yourself that would be highly accurate and easy to train. You vastly underestimate the difficulty to create a bespoke solution from scratch and no data. In any case since the supervisor thing was just an example - the original poster's only real choice is to manually label everything, but AI is really problem centric so it's hard to recommend anything without knowing the actual problem. Assuming it really is just [someone in an area for a period of time] kind of problem, and the difficulty is picking apart the 'someone' and you cannot influence their behavior, you just need massive amounts of data. Even then there's no guarantee you'll have high accuracy. If high accuracy is required the problem itself needs to be examined on a higher level.

SubiculumCode 7y ago

This is not bad, but once in this territory, why not just add some tracking beacon to a badge?

newfeatureok 7y ago
That is also a good idea. It really depends on what the rest of the requirements are.

Gatsky 7y ago

Reminds me of this: https://userweb.cs.txstate.edu/~br02/cs1428/ShortStoryForEngineers.htm https://userweb.cs.txstate.edu/~br02/cs1428/ShortStoryForEng...

deepGem 7y ago

This is a pragmatic and valid approach. No matter what anyone else says. Imagine, you told a 10 YO child to do this task. Even the child would ask the same question - how do I know who is a supervisor and who is not. Not only is face recognition hard, it is almost impossible to accomplish in a factory floor like setting. Not totally impossible but it is really really hard. Face detection is still possible but face recognition is far more computationally expensive. You'll need a shit ton of data and you'll need access to the employee database. You'll need a whole new engineering pipeline to make this happen and of course a team. Compared to that expense and time, you are way better off getting the company to approve special vests for supes.

coredog64 7y ago
I remember hearing a similar story circa 2003-2008. Some BigCo was spending a bunch of money to automate their inter office mail and was hung up on OCR of handwritten stuff. Some consultants come in to look and one asks if they can just use different color envelopes/baskets. The answer was “yes”.

asiachick 7y ago

Just passing on info but ANA (the airline company) has colored helmets in their maintenance to facility to distinguish supervisors (color 1) from non supervisors (color 2) and 1st year employees (colors 3) and guests (color 4). I don't know if they do any tracking.

fareesh 7y ago
This example was totally made-up. In my experience related to the type of arrangement you're describing - in reality (at least anecdotally speaking) the helmets are often not worn, or the colors are not enforced, or the colors don't get picked up due to poor quality video. I deal mostly with third-world countries so safety standards are not always the best.