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Hello!

I would advise you to use traincascade app. haartrainig is an obsolete version of a cascade training, it's less supported and does not develop. Once, in one of the following revisions, you can not find it. traincascade is the newer c++ app for the training. In contrast to haartraining trancascade supports not only Haar features, but LBP too (and as I know HOG too). See the doc.

But keep in mind that if you use Haar features you'll not see a significant difference in time of training for both apps, because they do the same work in this case. You should try the LBP features instead of Haar if you want to train a cadcade within ~hour instead of ~day (with default parameters, ie with larger positive and negative examples count than you used). LBP features are also ~3 times faster than Haar in the detection (they are real-time on mobile platforms on VGA).

So your best bet is traincascade + LBP.

Hello!

I would advise you to use traincascade app. haartrainig haartraining is an obsolete version of a cascade training, it's less supported and does not develop. Once, in one of the following OpenCV revisions, you can not find it. traincascade is the newer c++ app for the training. In contrast to haartraining haartraining, trancascade supports not only Haar features, but LBP too (and as I know HOG too). See the doc.

But keep in mind that if you use Haar features you'll not see a significant difference in time of training for both apps, because they do the same work in this case. You should try the LBP features instead of Haar if you want to train a cadcade within ~hour instead of ~day (with default parameters, ie with larger positive and negative examples count than you used). LBP features are also ~3 times faster than Haar in the detection (they are real-time on mobile platforms on VGA).

So your best bet is traincascade + LBP.