
Using neural networks to detect car crashes in dashcam footage - gk1
https://blog.insightdatascience.com/crash-catcher-detecting-car-crashes-in-video-9c0522b04558
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matt4077
The source, as well as more in-depth description, is available at
[https://github.com/rwk506/CrashCatcher](https://github.com/rwk506/CrashCatcher)

This is actually quite neat! Having little data and not enough resources to
manually label thousands of examples seems to be a somewhat neglected problem.
Maybe we should boycott Google's captchas until they feel the same pain :)

The comments in the code do read like a parody, though:

    
    
        count = 0  ### start a counter at zero

~~~
nl
_Having little data and not enough resources to manually label thousands of
examples seems to be a somewhat neglected problem._

It's not a neglected problem - it is an extremely active area of research, and
something people deal with every single day when using ML in industry (do you
feel my frustration there?!)

The problem is that there isn't a single generalization method that works
well.

For specific problems there are numerous approaches which can help. Distant
supervision, adversarial techniques, data augmentation, reinforcement learning
etc are all areas to look at - but the specific technique depends on your
exact problem.

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djaychela
As someone who's interested (but not remotely capable yet) in this sort of
thing, I think it would have been nice to see some more detail as to how the
system worked - this seemed more of an executive summary to me rather than
giving any significant technical details; is this true or is it my lack of
knowledge showing?

~~~
Drdrdrq
To me this level of detail is perfect - but I do have some prior knowledge on
the subject. I think it is difficult to put such a project in writing in more
detail because many choices (framework, NN architecture, data cleanup
procedures...) make sense only with data which probably can't be shared. So I
think author did a great job selecting those pieces of information which are
relevant to general public.

Btw, there are courses, tutorials and challenges online if you ever wish to
learn more... It is fairly easy to get good info, but it takes time to grasp
concepts. It is fun though and enables you to solve a whole new class of
programming challenges. :)

~~~
sillysaurus3
_Btw, there are courses, tutorials and challenges online if you ever wish to
learn more... It is fairly easy to get good info, but it takes time to grasp
concepts. It is fun though and enables you to solve a whole new class of
programming challenges. :)_

Any tips? Which classes would you recommend?

~~~
Drdrdrq
Well, I myself actually usually prefer text to video, so I just search for
tutorials and read the ones that I feel I understand... So I can't really
recommend any classes (but if you see Karpathy listed as author then it's
probably good :)). Do check out Kaggle - there is nothing better than playing
with the best and learning from them.

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rasz
80% for 4 second clips, so running it on random video feed guarantees false
positives in under a minute.

Not to mention this is trying to predict something human expert in the field
(lets say a taxi driver) watching same clips couldnt do, its trying to predict
future. Most likely triggers on something semi related, like amount of cars in
front/roundabouts/red light, more cars = bigger chance of accident = strong
correlation. Garbage in garbage out.

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kalal
I would like to see how the system generalizes on different videos. The motion
pattern seems to be quite general ... this can be used to analyze crashes
during racing events for instance
([http://www.tldvision.com/tld3.html](http://www.tldvision.com/tld3.html)).

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amelius
The author could also have used 3d simulations to obtain more data, and
determine feasibility and proper hyperparameters for the network before
training with actual data.

~~~
minimaxir
3D simulations can’t create _photorealistic images_. (Not currently, anyways)

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bkberry352
You don't need photorealistic images for these situations. The images are
always downsampled to a smaller resolution. So getting "good enough" but not
photorealistic is fine.

~~~
minimaxir
If you have software to simulate real-world physics for hundreds of
independent agents that can be run on a personal computer with _close_ to real
world graphic fidelity (including realistic noise), you’re running a
_multibilion dollar company_ , not writing thought pieces on Medium.

~~~
nl
There are a few companies you can get simulation software from specifically
designed for self-driving cars. See
[https://blogs.nvidia.com/blog/2017/10/26/self-driving-
simula...](https://blogs.nvidia.com/blog/2017/10/26/self-driving-simulation/)
for some discussion.

It's true that this isn't photo-realistic (see
[https://www.youtube.com/watch?v=D7OccC0W_CU](https://www.youtube.com/watch?v=D7OccC0W_CU)
for a video), but at the same time it is useful enough for training.

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kakali
Can't they just use an accelerometer?

~~~
mikeash
It looks like they are detecting crashes of _other_ cars caught on camera, not
crashes of the car with the camera.

