Design facial appearance for roles in video games

Roles in video games often serve as avatars of players. Different game players may have their particular preferences on a role’s facial appearance. It would be desirable to allow players to customize the design of roles. This paper presents two methods for recommending a roles’ facial appearance for a particular game player and illustrates the two methods by using heroic roles as an example. The two recommendation methods are designated as the text-input and the picture-input approaches. The text-input approach requests the game player to carry out pairwise comparisons for determining the relative weights of 16 personality traits of heroes. The recommendation mechanism for the text-input approach is based on the fuzzy AHP (analytic hierarchy process). Whereas the picture-input approach requests the game player to view a sample set of pictures and rate his/her preferences on each picture. The recommendation mechanism for the picture-input approach is based on the BP (back-propagation) neural network. Experiments indicated that the text-input approach is more effective in terms of recommending an appropriate facial appearance, yet at the expense of needing more user time.