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Color Detection

developers.lyst.com

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11–20 of 27 posts

Re: Color Detection

#11

Post by tsumnia »

ejlb wrote: post #3
tsumnia wrote: post #2

Really cool techniques (this is the background removal one). I'm curious on how well this would work on hair color detection. My thoughts are that you could run face detection, and since detection almost always (anecdotal) find just the face, not the outline of the face, you could just grab around the face for hair. Does someone at Lyst have a background in image manipulation? If so, I can't wait to see what else you…

Most of the guys here have more experience with text processing but we are expanding into image processing. I think we could definitely detect hair colour but it isn't that useful for Lyst. Gender identification on the other hand...(watch this space)

I'll be curious about the gender classifier, mostly because I'm working on a statistical aging model for different gender/ethnicities. Keep on posting!

Re: Color Detection

#13

Post by Bjoern »

raarky wrote: post #4

Nice. I'm building something similar in my spare time. It performs multi-color image searching on street wear. You can select a bunch of colors and adjust the ratios. Here's a very early in-development version. http://www.inthatstyle.com/womens?colors=73a1d3,e84b34&ratio... (I'm a little worried about posting that on HN since it's unoptimized and will probably crash.) I'm currently working on skin detection & exclusi…

Nice! Here is another player in this field (fyi). http://labs.tineye.com/multicolr

Re: Color Detection

#14

Post by vision_cat »

Nice post. I'm a researcher in computer vision, so I'm glad to see that people find these problems interesting. It's often easy to underestimate how difficult vision problems are, since they seem so natural to us.

I think the recent posts by lyst (this color naming post, and the previous background subtraction post) are great introductions to problems in computer vision. However, there is a lot more sophisticated work out there, and the techniques used in these posts are decades old (and contain some errors).

If you liked this post, you should check out this more recent demo http://clothingparsing.com/

If you have a computer vision problem in mind, you can gauge the state-of-the-art, by searching recent papers on Google Scholar. Even if you're unfamiliar with the jargon, the introduction and conclusion of a paper can give you an intuition about the problem being solved and the steps the authors are proposing.

If you want to learn more about computer vision and its details, I highly recommend checking out online materials such as

http://cs.brown.edu/courses/cs143/

http://www.cs.cornell.edu/courses/cs4670/2013fa/lectures/lec...

http://szeliski.org/Book/

Re: Color Detection

#15

Post by strebler »

Color is actually much more difficult than most people realize! Even CIE2000 color distance still has fundamental "perceptual distance" problems, especially comparing non-saturated with saturated colors (although that's a blog post in its own).

Here's our engine linking "real world" photos into the Macys catalogue (based on color, shape, texture): http://www.pcsso.com/demo/macys.htm

Re: Color Detection

#16

Post by Bjoern »

strebler wrote: post #15

Color is actually much more difficult than most people realize! Even CIE2000 color distance still has fundamental "perceptual distance" problems, especially comparing non-saturated with saturated colors (although that's a blog post in its own). Here's our engine linking "real world" photos into the Macys catalogue (based on color, shape, texture): http://www.pcsso.com/demo/macys.htm

Yeah, totally agree on that. We noticed this as well when approaching it naively via simple clustering then going through different color spaces and methods until finally getting some decent results.

Re: Color Detection

#17

Post by Bjoern »

vision_cat wrote: post #14

Nice post. I'm a researcher in computer vision, so I'm glad to see that people find these problems interesting. It's often easy to underestimate how difficult vision problems are, since they seem so natural to us. I think the recent posts by lyst (this color naming post, and the previous background subtraction post) are great introductions to problems in computer vision. However, there is a lot more sophisticated wor…

Nice! Clothingparsing very cool.

Re: Color Detection

#18

Post by adyus »

ejlb wrote: post #3
tsumnia wrote: post #2

Really cool techniques (this is the background removal one). I'm curious on how well this would work on hair color detection. My thoughts are that you could run face detection, and since detection almost always (anecdotal) find just the face, not the outline of the face, you could just grab around the face for hair. Does someone at Lyst have a background in image manipulation? If so, I can't wait to see what else you…

Most of the guys here have more experience with text processing but we are expanding into image processing. I think we could definitely detect hair colour but it isn't that useful for Lyst. Gender identification on the other hand...(watch this space)

That's a very sensitive area to be heading into. Any assumptions you might try to make will find themselves with counter-examples quite often.

A better direction to move in might be to minimize gender differences as much as possible (although that's hard for marketing to stomach).

I mean, would one try not to recommend pants for girls or skirts for boys (kilts)? It's tricky...

Re: Color Detection

#19

Post by TheZenPsycho »

"To speed up the color difference calculations we decided to vectorised deltaE. The standard deltaE functions are already implemented in the colormath python package. We ported these to numpy and added a function to take a numpy array of Lab coordinates. When used with large data-sets the vectorised implementation is 25-180 times faster depending on which distance function is used. The vectorised delta E functions are now available in the colormath package and can be used in the following manner."

Uhm.. wouldn't it have been easier to just run a voronoi algorithm on the data set in the labspace? then you have a lookup table/cube. For a paltry 6mb of space, lookup becomes instantaneous. It's what voronoi is for.

Re: Color Detection

#20

Post by ejlb »

vision_cat wrote: post #14

Nice post. I'm a researcher in computer vision, so I'm glad to see that people find these problems interesting. It's often easy to underestimate how difficult vision problems are, since they seem so natural to us. I think the recent posts by lyst (this color naming post, and the previous background subtraction post) are great introductions to problems in computer vision. However, there is a lot more sophisticated wor…

Thanks for all the great resources. I think it must be obvious that we aren't image processing researchers! My background is combinatorial graph theory. But these HN comments have given us so much valuable material for improvements.
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