Can 2 dimensional input be applied to SVM?
If I understand your question correctly. Yes, SVM can take multiple inputs. My suggestion for handling a vector as a feature would be to expand it out. For example,

x0 = (1,2)       x0 = 1
x1 = .4  -----&gt;  x1 = 2
x2 = 0           x2 = .4
                 x3 = 0


If this does not capture all of the characteristics of the vector that are important, then you may want to add other features (like magnitude of the vector) as well.