自动我的小马驹检测和分类 [英] Automated My Little Pony detection and classification

问题描述

我要寻找的是具有计算机视觉经验的人的建议，在这个问题上什么方法或算法是最好的。我是一个有经验的程序员（大多是.NET），但我知道没有什么关于计算机视觉，我想节省时间。

What I'm looking for is advice from people with experience with computer vision on what approach or algorithm would be best on this particular problem. I'm an experienced programmer (mostly .NET), but I know next to nothing about computer vision and I want to save time.

我要检测的内容：



独特的颜色，锐利的边缘，缺乏渐变和很少的噪音。

What I want to detect:

Distinctive colors, sharp edges, lack of gradients, and very little noise.

我想象的最终结果是像Picasa或Windows Live Gallery做的 - 我标记

I envision the end result to be something like what Picasa or Windows Live Gallery does - I mark a pony in a few images and the program finds other images containing the same pony.

推荐答案

漫画家在他们的绘画中获得特别强的许可证与未修饰的照片。因此，尝试通过颜色识别Pinkie馅饼在一个框架中做了很多好，她已经落入一桶黑色油漆。或者你可能认为你可以通过她的角标识稀有，但考虑到她希望她可以是一个普通的小马的剧集...但失去了她的角后，她学会了一个关于自己的教训。

Cartoonists take particularly strong license in their drawings vs. an unretouched photo. Thus trying to identify Pinkie Pie by color doesn't do a lot of good in a frame where she has fallen into a vat of black paint. Or you might think you could identify Rarity by her horn, but consider the episode where she wishes she could be a regular pony...but after losing her horn she learns a lesson about being oneself.

True。这是真的。

True. So true.

这意味着，取决于你在这里做什么和规模，它可能是有意义的，为众包系统提供一个接口。如果你没有看到白手套项目，你可能会发现一些灵感：

This means depending on what you're trying to do here and the scale of it, it may make sense to provide an interface to a crowdsourcing system. If you haven't seen the white glove project, you might find some inspiration in that:

http://whiteglovetracking.com/

它不一定是全自动或手动的。您可以使用多种技术的组合，并在有不确定性阈值时引入人工编辑器。

It doesn't have to be all automatic or manual, though. You could use a combination of techniques, and bring in human editors whenever there's a threshold of uncertainty.

对于设计启发式算法，似乎是开始获取小马的地方是寻找眼睛的感觉。开始搜索小马形状的东西可能是一个有点失去的原因...特别是如果这些是框架从卡通可能有特写镜头。事实上，看看这里的例子，独角兽只是一个头！

As for designing a heuristic, it seems the place to start in getting a sense of where ponies are is to look for the eyes. Beginning with a search for "pony shaped things" might be a bit of a lost cause...especially if these are frames from a cartoon which might have close ups. In fact, looking at just your example here, the unicorn is just a head!

我建议的下一步是在眼睛周围看一定半径用于匹配头发和身体的颜色块。所有的我的小小马在我的收藏有独特的头发和身体的颜色，和... 等待...我的意思是我不知道如果我的小小马的字符有独特的颜色组合或没有！ ！

The next step I'd suggest would be to look in a certain radius around the eyes for color blocks matching hair and body. All of the My Little Ponies in my collection have unique hair and body colors, and...wait...I mean I don't know if My Little Pony characters have unique color combinations or not!! But they probably do.

一旦你输入了小马的颜色指纹，然后你可以进一步搜索，并可能通过使用类似洪水填充算法得到一个边界框，假设小马是没有孔的单一多边形。再次，眼睛可以给你一个好主意，小马可能会在图片中有多大，但再次卡通人可以打破这种期望在任何时刻。加上小马关闭他们的眼睛或眨眼等，所以你在这里做的任何事情都需要审查。

Once you've intuited the pony's color fingerprint you can then search further and probably get a bounding box by using something like a flood-fill algorithm, assuming ponies are single polygons with no holes. Once again the eyes can give you a good idea of how large the pony will likely be in the picture, but once again cartoonists can break that expectation at any moment. Plus ponies close their eyes or blink etc. so anything you do here is going to need vetting.

（注意：如果你有一个完整的视频流，你可以想象使用帧间分析来处理眨眼的问题，更普遍的是大多数情况下，小马是最动画的东西，在大多数其他静态框架 - 这可能加强你的信心，启发式发现他们。）

(Note: If you've got an entire video stream, you could conceivably use inter-frame analysis to finesse issues of blinking. More generally, it is probably the case that the ponies are the "most animated" things in most otherwise static frames--that may bolster your confidence in a heuristic for finding them.)

但是无论你做什么选择做...记住，友谊是魔术 - 图像识别!!

But whatever you do choose to do...remember that Friendship Is Magic--and so is Image Recognition!!

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