The deformable part based model is pretty much /the/ state-of-the-art object detection model. There is absolutely no way it should be attributed to "Liu Liu". It's creators are Felzenszwalb et al.[1].
The performance of DPMs far surpasses any other basic model such as a Viola Jones syle Haar cascade. Also you should find with DPMs that you are able to detect faces with far higher degrees of deformation - i.e. 3/4 profile faces, rotated faces etc. DPMs are far far more robust than haar cascades but with greater computational expense. Check out the papers at [1].
I was using "Liu Liu's algorithm" in a colloquial way. Should have been more specific and used, "the algorithm which Liu Liu implemented".
As far as robustness is concerned I guess a lot depends on the quality of the training. The haar-caascade used in openCV is very well trained and generates few false +/-'ves. I wanted to know how this particular implementation of DPM performed.
The performance of DPMs far surpasses any other basic model such as a Viola Jones syle Haar cascade. Also you should find with DPMs that you are able to detect faces with far higher degrees of deformation - i.e. 3/4 profile faces, rotated faces etc. DPMs are far far more robust than haar cascades but with greater computational expense. Check out the papers at [1].
[1] http://www.cs.brown.edu/~pff/latent/