Combining multi-class maximum margin classification with linear discriminant analysis for human action recognition
Alexandros Iosifidis, Moncef Gabbouj · 2016
In this paper, a new multi-class classification method is proposed and evaluated in the problem of human action recognition in unconstrained environments. The proposed method exploits both the maximum margin property of multi-class Support Vector Machines and Linear Discriminant Analysis-based discrimination. Experiments indicate that by exploiting such discriminant information in a multi-class maximum margin framework, classification performance can be enhanced, leading to state-of-the-art performance in human action recognition.