Hello all. I've been given an assignment at Uni but I only have 10 days to do it, and I know very little about the subject, so I'm after some advice and/or suggestions of tutorials/guides that may help me. The task is: "The purpose of this assignment is to implement an appearance-based program in C/C++ to recognise an object based on a learnt model of the appearnce of the object" "The minimal requirement is to construct an eigenspace representation of a set of sampled images of an object, and use this subsapce to perform object recognition" We get additional marks depending on the complexity of the program, e.g. using multiple objects, using SVD, robust statistics etc. However I'm not really fussed about this at this stage. So far I've loaded the test images in (using C btw), and calculated the average image of all the input images. But now I'm not really sure what to do. I've read about a covariance matrix and I think that is the next step but I'm not sure what I do with it. I'm also unsure as to the part eigenimages, eigenspaces and eigenvectors play in the whole recognition process. Any advice? Thanks very much.