Rhonda Software

Highest quality full cycle software development.

Expert in areas of Computer Vision, Multimedia, Messaging, Networking and others. Focused on embedded software development. Competent in building cross-platform solutions and distributed SW systems.

Offer standalone custom solutions as well as integration of existing products. Opened for outsourcing services.

Visit us at: http://www.rhondasoftware.com

Fast & Furious face detection with OpenCV

Posted on : 18-06-2009 | By : rhondasw | In : OpenCV

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In OpenCV/Samples there is  facedetect program.  This program can detect  faces on images and video.  It’s very fun, but its speed leaves much to be desired =(.  Of course  with OpenMP,  it works  faster; on Intel Core Duo 2.7GHZ, it works fast;  but will it work fast on ARM? I have big doubts.  I compiled facedetect without OpenMP and on average it takes 600 ms for 640×480 resolution to find one face.   I wanted to find out, if it’s possible to improve this time by software means or not…  After some investigations, code refactoring and improvements, facedetect started to work 2.5 time faster, even on ARM.  Of course, without big quality loss =)

“Fixing” the OpenCV’s implementation of Viola-Jones algorithm

Posted on : 10-04-2009 | By : rhondasw | In : OpenCV

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Today’s story is about improving performance of OpenCV library on the ARM-based platforms.

As you already know (from here or from here or may be even from here), face detection algorithm implemented by OpenCV library doesn’t work perfectly on ARM processors. Science doesn’t know for certain why this happens. There might be several possible reasons. One of our assumption was missing of hardware support for floating point operations. So we tried to translate Viola-Jones algorithm from floating point to fixed point. And that’s how we did this…