I want to optimize my face detection algorithm by scaling down the image. What is the best way? should I use cvPyrDown (as I saw in one example and yielded poor results so far), cvResize or another function?
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I want to optimize my face detection algorithm by scaling down the image. What is the best way? should I use cvPyrDown (as I saw in one example and yielded poor results so far), cvResize or another function?
If you only want to scale the image, use
cvResizeas Adrian Popovici suggested.cvPyrDownwill apply a Gaussian blur to smooth the image, then by default it will down-sample the image by a factor of two by rejecting even columns and rows. This smoothing may be degrading your performance (I’m not sure how it affects the detection algorithm). Another possibility for the poor performance might be the discontinuities created by just dropping even rows and columns; whereas, the smooth interpolations (assuming you interpolated with something other than nearest neighbor) bycvResizeallow the face detection to work better. Here is the documentation oncvPyrDownfor more information on the exact kernel that is used.