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I work in the AV space. There's a lot of ambiguity in labeling. How should a crowd of people be annotated? A line of parked cars? A photograph of a car? Exami

I work in the AV space. There's a lot of ambiguity in labeling. How should a crowd of people be annotated? A line of parked cars? A photograph of a car? Examine the training set!

CydeWeys 7y ago
A line of parked cars absolutely needs to be labeled as individual cars. Any one of them could pull out in front of you at any moment.
- wlkr 7y ago
  Indeed, whilst additionally presenting the chance of a door opening or an obscured pedestrian stepping out from between them.
  - CydeWeys 7y ago
    Yup. You need to consider not only what you can see, but what you can't see. And this is a harder problem.
TACIXAT 7y ago
Are there any studies on how this affects recognition? I'm labeling some vehicles and will my neural net learn better (for say vehicle identification) from a row of identical vehicles, individual vehicles with overlap, non-overlapping parts only?
PeterisP 7y ago
A big thing is not that the example is missing, but that it counts as a negative example. I.e. if during training a ML system notices the ambiguous combination (i.e. a woman pushing a baby stroller or a crowd) and marks it as a pedestrian, then it gets penalized in a manner that teaches it to ignore these ambigious combinations and treat it as nothing; while in practice it should probably treat such ambiguous combinations as even more "avoid-worthy" as an ordinary pedestrian. The problem is that the default assumption is "clear road, you can drive there" - so what we need isn't "pedestrian detection" that finds pedestrians and only pedestrians, we need detection of random stuff that you shouldn't drive over. If a kid is wearing a weird Halloween costume, that doesn't look like a pedestrian, but it is one; If somebody has set up a tent in the middle of a supermarket parking lot, that's not a pedestrian but it should be avoided just like one.
- myself248 7y ago
  Likewise, I have yet to see one of these things that can recognize potholes and swerve to avoid them lest a wheel be ripped off. Sooner or later it'd be nice to be able to drive one of these things in a place that isn't southern California.
  - jacquesm 7y ago
    That's a feature, not a bug. Swerving for potholes can be very dangerous, more dangerous than having undercarriage damage. If a pothole surprises you enough that you have to swerve you were either not paying attention to the road or you are following too close.
    - notahacker 7y ago
      tbf there's still the evaluate whether slowly changing your lane position to avoid the pothole will impede or confuse other road users, and do so only if that isn't the case option to avoid potholes, and I don't imagine [semi]autonomous driving systems do that either?
    - PeterisP 7y ago
      Regardless of what's the appropriate action to take given the context (ignoring, swerving, slowing down, a timely proper change of lane) it's probably not controversial that potholes should be identified by a car vision system and taken into account. And from a computer vision perspective there's no qualitative difference between "just" a deep pothole and a lane-wide ten foot deep sinkhole or a construction pit that's unmarked for some reason, it's just a matter of size.
- wnoise 7y ago
  Right, what's really needed is a "clear road detector".

I work in the AV space. There's a lot of ambiguity in labeling. How should a crowd of people be annotated? A line of parked cars? A photograph of a car? Examine the training set!

CydeWeys 7y ago

A line of parked cars absolutely needs to be labeled as individual cars. Any one of them could pull out in front of you at any moment.

wlkr 7y ago
Indeed, whilst additionally presenting the chance of a door opening or an obscured pedestrian stepping out from between them.
- CydeWeys 7y ago
  Yup. You need to consider not only what you can see, but what you can't see. And this is a harder problem.

TACIXAT 7y ago

Are there any studies on how this affects recognition? I'm labeling some vehicles and will my neural net learn better (for say vehicle identification) from a row of identical vehicles, individual vehicles with overlap, non-overlapping parts only?

PeterisP 7y ago

A big thing is not that the example is missing, but that it counts as a negative example. I.e. if during training a ML system notices the ambiguous combination (i.e. a woman pushing a baby stroller or a crowd) and marks it as a pedestrian, then it gets penalized in a manner that teaches it to ignore these ambigious combinations and treat it as nothing; while in practice it should probably treat such ambiguous combinations as even more "avoid-worthy" as an ordinary pedestrian. The problem is that the default assumption is "clear road, you can drive there" - so what we need isn't "pedestrian detection" that finds pedestrians and only pedestrians, we need detection of random stuff that you shouldn't drive over. If a kid is wearing a weird Halloween costume, that doesn't look like a pedestrian, but it is one; If somebody has set up a tent in the middle of a supermarket parking lot, that's not a pedestrian but it should be avoided just like one.

myself248 7y ago
Likewise, I have yet to see one of these things that can recognize potholes and swerve to avoid them lest a wheel be ripped off. Sooner or later it'd be nice to be able to drive one of these things in a place that isn't southern California.
- jacquesm 7y ago
  That's a feature, not a bug. Swerving for potholes can be very dangerous, more dangerous than having undercarriage damage. If a pothole surprises you enough that you have to swerve you were either not paying attention to the road or you are following too close.
  - notahacker 7y ago
    tbf there's still the evaluate whether slowly changing your lane position to avoid the pothole will impede or confuse other road users, and do so only if that isn't the case option to avoid potholes, and I don't imagine [semi]autonomous driving systems do that either?
  - PeterisP 7y ago
    Regardless of what's the appropriate action to take given the context (ignoring, swerving, slowing down, a timely proper change of lane) it's probably not controversial that potholes should be identified by a car vision system and taken into account. And from a computer vision perspective there's no qualitative difference between "just" a deep pothole and a lane-wide ten foot deep sinkhole or a construction pit that's unmarked for some reason, it's just a matter of size.
wnoise 7y ago
Right, what's really needed is a "clear road detector".