Face-based difficulty adjustment for the game five in a row

Abstract

History of the logic games like chess, checkers or five in a row as is old as humanity itself. Primary goal of these games is to train the human brain with a thinking on the future moves. Idea is that the winner is that one with the most successfully predicted moves. Any help for this goal is more than welcome. In current day there is trend to brings all games to our SmartPhones to fill the free time by a possibility of play at any place anytime. There is a many existing solutions, application and ideas how design graphical user interface of these game applications, where the actual trend is to make an intelligent computer opponent with some intelligence which has no standard (all time same) strategy or starting parts. The goal of this paper is to use some standard algorithms like Minimax or Alpha-Beta with the help of user/player face detection usable for difficulty level adjustment. This is described in whole paper step by step as design as well as implementation issues related to appropriate parts of solution. Face detection is used to indicate meta-info of the player by the help of front camera of SmartPhone. This meta-info as age, sex or mood is evaluated and is taken as input for difficulty adjustment not only at start of every game, and even in every move, what make a playing this game amazing.