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Face detection jQuery Plugin

facedetection.jaysalvat.com

41–43 of 43 posts

Re: Face detection jQuery Plugin

#41

how much of your donations are going to Liu Liu, the original author of the hard part of this piece?

I suspect the developer has only received enough money for 2 beers. Aside from that almost all of us here build you livelihood on-top of open source tools. How much money did your startup give back to the Apache foundation, to the Django or Rails projects?

Re: Face detection jQuery Plugin

#42
post #15

Earlier quoted context omitted.

It's not just the algorithm, the whole detection code is just cutpasted from liu liu's repository. https://github.com/liuliu/ccv/blob/stable/js/ccv.js

The sheen is coming off this quite rapidly.

The sheen is the product in this case. Jay took this wonderful obscure code and wrapped it up nice and pretty to share with others. The examples and docs he provides were enough to allow me to use this plugin. That is the value the provides.

Re: Face detection jQuery Plugin

#43
post #16
post #12

Looks like more evidence for Atwood's Law: Any application that can be written in JavaScript, will eventually be written in JavaScript. I have a couple of questions: 1. How does Liu Liu's algorithm (which I think he calls "deformable parts model") compare with Viola-Jones [1]? Any idea what the error stats (false positives & negatives) are like? In my experience [2] Viola-Jones has very low error rates. Regarding per…

The deformable part based model is pretty much /the/ state-of-the-art object detection model. There is absolutely no way it should be attributed to "Liu Liu". It's creators are Felzenszwalb et al.[1]. The performance of DPMs far surpasses any other basic model such as a Viola Jones syle Haar cascade. Also you should find with DPMs that you are able to detect faces with far higher degrees of deformation - i.e. 3/4 pro…

I was using "Liu Liu's algorithm" in a colloquial way. Should have been more specific and used, "the algorithm which Liu Liu implemented".

As far as robustness is concerned I guess a lot depends on the quality of the training. The haar-caascade used in openCV is very well trained and generates few false +/-'ves. I wanted to know how this particular implementation of DPM performed.

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