Comments on: Parallel world of OpenCV (HaarTraining)

By: Vanja

Vanja — Sat, 26 Dec 2009 18:18:15 +0000

Hi Aleksey,

I’m interested in part “Results are very similar” – were there any significant differences in generated cascade?

Regards,
Vanja

By: Victor

Victor — Mon, 30 Nov 2009 13:15:39 +0000

Hi,

nice article and interesting idea.

I think it would be interesting to see the results of this experiment, reduced computing time is just one of the results, but what about performance?

Could you please post the results given by the performance tool comparing your cascade with the one generated with a single computer?

Thank you!

Best regards,
Victor

By: Computer Vision Software » Blog Archive » FAQ: OpenCV Haartraining

Computer Vision Software » Blog Archive » FAQ: OpenCV Haartraining — Fri, 13 Nov 2009 02:07:03 +0000

[...] Yes, one of possible ways is to use parallel programming. We have realized OpenCV haartraining using MPI for linux cluster. You can read it here [...]

By: Aleksey Kodubets

Aleksey Kodubets — Fri, 18 Sep 2009 08:34:52 +0000

Great!

By: Nick

Nick — Thu, 17 Sep 2009 14:06:24 +0000

Hi, Thankyou.

I read that on a previous post after I made the post. I have already sent a request on the about page a few hours ago as per the instructions and look forward to hearing a reply.

Nick

By: Aleksey Kodubets

Aleksey Kodubets — Thu, 17 Sep 2009 11:00:26 +0000

Hi Nick,

We could answer on your specific questions. Our management doesn’t allow to share the code here on blog. If you would like to have our code, please see “about” page regarding details how to contact to our marketing team.

Aleksey

By: Nick

Nick — Thu, 17 Sep 2009 07:03:56 +0000

Hi Would it be possible to get some assistance or code for haartraining project with the changes mentioned for MPI as we are planning to use an scalable HPC linux cluster service to process a very large number of very complex cascades.

Any help would be greatly appreciated

By: Vasiliy Mun

Vasiliy Mun — Thu, 03 Sep 2009 23:30:14 +0000

You can use PCA method to get features and then use another binary classificator like NBC.

http://www.codeproject.com/KB/audio-video/haar_detection.aspx

By: Mukund

Mukund — Wed, 02 Sep 2009 18:39:53 +0000

Hi John,
Thanks a lot, I found your link very useful for my project. I am trying to implement the haar classifier on an FPGA and I am having difficulties in fixing the number of classifiers. I found that most boost algorithms generate 1000′s of haar features. Are there any other algorithms which use fewer number of classifiers without compromising on detection rates?. I am aiming for detection rates of 80 to 85% and false positive rates of 5 to 10%

By: Aleksey Kodubets

Aleksey Kodubets — Sun, 23 Aug 2009 01:35:05 +0000

Hi Rudy,

This arctilce has enough details. Can you please specify your question with more details? What particular more guidance you need?

->feasibility,
[Aleksey] Yes, it is feasible as per this article.

->where starting point,
[Aleksey] MPI as stated with this article.

->reference paper etc).

[Aleksey] There is no such, we didn’t find and thus write this one.

Unfortunaly we cannot share our code but you can see “about” page and contact to our marketing team for getting source code or asking our help.