Regarding to "Object Recognition with Informative Features and linear classification".
This method of trying to detect objects using fragments of it reminds me eigen-based methods. It is a similar approach in which instead of using fragments of the object usually a small set of bases are used to represent all possible views of the entire object. These methods usually perform better than simple cross-correlation as tend to eliminate outliers and are faster since fewer basis are needed to encode the object. I would like have seen a comparison of this method with eigen methods.