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Like @GilLevi already pointed out, you are looking to the wrong set of algorithms. You need a body part detection algorithm designed for these purposes. Techniques that come in mind to me are

1. LatentSVM, discovered by Felzenszwalb : http://www.cs.berkeley.edu/~rbg/latent/
2. Class specific hough forests by Gall and Lempitsky : http://www.vision.ee.ethz.ch/~gallju/projects/houghforest/
3. The buffy stickman approach of the Calvin group : http://www.robots.ox.ac.uk/~vgg/data/stickmen/
4. The integral feature channel approach of dollar is also in possibility of detecting more complex models and could be combined with checking multiple rotations : http://vision.ucsd.edu/sites/default/files/dollarBMVC09ChnFtrs_0.pdf

But keep in mind that these techniques are active research topics, quite complex and they will not be available off the shelf in OpenCV. There is a basic LatentSVM detector class but it works rather slow and is totally not optimized (was based on the first implementation of Felzenszwalb)