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It is known that Haar is not good for human body detection. You're right, you may have problems with number of both positive and negative samples (do you have thousands of unique images?), you may also have problems with how you cut positives, but the root cause should be that Haar features are not good for such task. And I suppose that LBP is not good as well.
You should better look into HOG direction, check this paper: Navneet Dalal and Bill Triggs, Histogram of oriented gradients for human detection. 2005. You can try to use the existing cascade: http://code.opencv.org/projects/opencv/repository/revisions/master/changes/data/hogcascades/hogcascade_pedestrians.xml. You can even try it on GPU with CUDA: http://docs.opencv.org/modules/gpu/doc/object_detection.html?highlight=hog#gpu-hogdescriptor.
