Neural network example to classify multi-dimensional features into two sets
In reality, all these machine learning techniques have their pros and cons. In using NN (single layer perceptron), you need to consider if you have enough training data. Technically speaking, you need to be able to cover all cells inside the dimensions to have a good result.
SVM on the other hand, tries to find a border separating your data points so if you have gaps in the areas which are not close to this border, it is fine.
There are 5-6 classifiers around +/- boosting and to be honest, it seems that most of the time type of the classifier is chosen subjectively. On the other hand, some people use multiple classifiers and compare the result.
With OpenCV, it is so easy to pluggin a different classifier so you are on right track for it. I used OpenCV in C++ with NN classifiers for my project and result was very good:
http://www.springerlink.com/content/j0615767m36m0614/