Parameterized generation of Avatar face dataset
Virtual communities such as Second Life and Entropia Universe are quickly becoming the next frontier of cybercrime. With GDPs of virtual economies of persistent worlds approaching billions of dollars it is necessary to develop tools for protection of virtual environments similar to those utilized to secure real world's infrastructure, such as biometrics security systems. The first step in the development of such security methodologies is wide availability of datasets necessary for training and testing of those biologically inspired systems. In this paper we present a manual and automated approach to generation of parameterized datasets containing facial images of avatars representing typical entities in the virtual worlds. Our work on making such standardized datasets makes it possible to develop novel security systems which function just like biometric recognition systems, but can be applied to recognition and verification of non-biological entities. © 2009 The University of Wolverhampton.