A model (In)validation approach to gait recognition
This paper addresses the problem of human gait recognition by applying model (in)validation techniques. The main idea is to associate to each class of gaits a nominal model and a class of bounded energy inputs. In this context, the problem of recognizing a sequence can be formulated as the problem of determining whether or not it could have been generated by a given model and its associated class of inputs. By exploiting interpolation theory results this problem can be recast into a Linear Matrix Inequality (LMI) optimization form and efficiently solved.