The short results are below. Just as a quick comment, due to the complexity of the dataset, several algorithms actually got negative score. That was expected, since these algorithms could't detect faces at arbitrary angles.
-FceOnIt ( http://www.idiap.ch/technology-transfer ... s/faceonit ) - 80 hits, 149 misses, 0 false positives, total score = -69
-Real Time Face detector from A. Telnykh ( http://www.torry.net/authorsmore.php?id=6639 ) using tilt face detector - 99 hits, 130 misses, 51 false positive, total score = -81
-OpenCV with Haar features - 96 hits, 133 misses, 50 false positives, ts = -87
-OpenCV with LBP features - 90 hits, 139 misses, 137 false positives, ts = -186
-BetaFace ( http://betaface.com/wpa/index.php/demo-gallery ) - 146 hits, 83 misses, 59 false positives, ts = 4
-Face++ ( http://www.faceplusplus.com/demo-detect/ ) - 139 hits, 90 misses, 3 false positives, ts = 46
So out of these six, I have an obvious winner.
More generally, the algorithms that detect facial features (eyes, nose, mouth etc) - the two last ones - performed much better than the other ones, mainly because they can handle tilted faces. Since for my application it is a must, I suppose that is what I should be focusing on.
I will post more detailed results once I get them into a nicer format...
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The programs that I wanted to try but couldn't are:
-Stasm from U of Capetown - http://www.milbo.users.sonic.net/stasm/ - require specific version of OpenCV that no longer can be downloaded from anywhere
-Face detection from U of Illinois - http://www.ifp.illinois.edu/~antonio/De ... Image.html - whatever image I gave it, just says that it couldn't recognize the format
-Online Face Detector from here: http://www.idiap.ch/~marcel/professional/Welcome.html - (apparently similar to FaceOnIt) - needs admin login (weird...)
-FDLib - http://people.kyb.tuebingen.mpg.de/kien ... /fdlib.htm - they only have precompiled old 32-bit dlls that I couldn't get to run.
P.S. Detailed data now posted.
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