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> Problem also looks like a good application for ML. Wouldn't that be complete overkill, though? Zooming and panning are so much simpler and less compute inten

by qayxc 6y ago

> Problem also looks like a good application for ML. Wouldn't that be complete overkill, though? Zooming and panning are so much simpler and less compute intensive.

theshrike79 6y ago
I think the idea was to find images that point to a certain location from a collection of photos. Not having a bunch of photos of people pointing and just zooming/panning to that bit.
- qayxc 6y ago
  ML methods would require labelled data to be trained. Labelling itself already solves the issue (i.e. a bunch of photos with people pointing in certain directions). So basically you'd solve the problem you want to solve in order to automate a task that you already performed.
  - nightcracker 6y ago
    > ML methods would require labelled data to be trained. Not necessarily. One could train a model on synthesized data using e.g. blender, some programmable 3D people models with hand controls and some generic background images to paste them on.
    - sillysaurusx 6y ago
      I've heard of this being used. It's surprising to hear you mention it. Have you done that? It's a neat idea, and I hope it becomes more popular.
      - nightcracker 6y ago
        > It's surprising to hear you mention it. Me specifically or in general? Anyway, for a Multimedia Information Retrieval course I chose to do my term project on training a neural network with synthetic data. In particular I modded Minecraft such that when I press a button it saves two screenshots: one regular and one where the game renders a depth map instead. I used this to generate ~1000 samples with perfectly accurate depth maps. Because of the mods, texture pack and world I used the data was somewhat realistic: https://i.stack.imgur.com/Zai51.jpg https://i.stack.imgur.com/Zai51.jpg https://i.stack.imgur.com/eamMR.png https://i.stack.imgur.com/eamMR.png This data was then used to train a neural network to predict the depth map of unseen images. It was relatively successful, but requires more data and more research, I only had so much time for a term paper.

by qayxc 6y ago

> Problem also looks like a good application for ML. Wouldn't that be complete overkill, though? Zooming and panning are so much simpler and less compute intensive.

theshrike79 6y ago

I think the idea was to find images that point to a certain location from a collection of photos. Not having a bunch of photos of people pointing and just zooming/panning to that bit.

qayxc 6y ago
ML methods would require labelled data to be trained. Labelling itself already solves the issue (i.e. a bunch of photos with people pointing in certain directions). So basically you'd solve the problem you want to solve in order to automate a task that you already performed.
- nightcracker 6y ago
  > ML methods would require labelled data to be trained. Not necessarily. One could train a model on synthesized data using e.g. blender, some programmable 3D people models with hand controls and some generic background images to paste them on.
  - sillysaurusx 6y ago
    I've heard of this being used. It's surprising to hear you mention it. Have you done that? It's a neat idea, and I hope it becomes more popular.
    - nightcracker 6y ago
      > It's surprising to hear you mention it. Me specifically or in general? Anyway, for a Multimedia Information Retrieval course I chose to do my term project on training a neural network with synthetic data. In particular I modded Minecraft such that when I press a button it saves two screenshots: one regular and one where the game renders a depth map instead. I used this to generate ~1000 samples with perfectly accurate depth maps. Because of the mods, texture pack and world I used the data was somewhat realistic: https://i.stack.imgur.com/Zai51.jpg https://i.stack.imgur.com/Zai51.jpg https://i.stack.imgur.com/eamMR.png https://i.stack.imgur.com/eamMR.png This data was then used to train a neural network to predict the depth map of unseen images. It was relatively successful, but requires more data and more research, I only had so much time for a term paper.