Re: [Vxl-users] benchmark on OpenCV book

[Wheeler, F. W (G. Research) <wh...@cr...>]

 
I'm not surprised to see VXL underperforming OpenCV in a neural net operation, since the word "neural" does not appear in the VXL source code.
 
The VXL vil 2D FFT implementation copies image data from each column and row to a vector, does the FFT on the vector, and copies the data back to the image again, if that data is not already in contiguous memory.  This stems from a requirement of vnl_fft_1d, and will usually happen for just the columns.  The vil FFT code does not take advantage of the special case of the data being real - it only operates on complex pixel values.  These issues could contribute to a performance differential.
 
Fred

 

________________________________

	From: Jorge Sanchez [mailto:jrg...@gm...] 
	Sent: Thursday, October 23, 2008 1:48 PM
	To: vxl...@li...
	Subject: [Vxl-users] benchmark on OpenCV book
	
	
	Hi all,
	I've found a performance benchmark on the recently edited OpenCV book. I attach a capture of the graph. Can anyone explain such differences? or in other way, what kind of optimizations are used?
	
	cheers,
	Jorge
	
	-- 
	Jorge A. Sánchez
	Centro de Investigación en Informática para la Ingeniería, CIII.
	Universidad Tecnológica Nacional. Facultad Regional Córdoba.
	Maestro M. López esq. Cruz Roja Argentina. CP X5016ZAA
	jsa...@sc...