On the design and player satisfaction evaluation of an immersive gestural game

Abstract

The role of human-computer interaction technologies has become a prominent factor that most can determine the successful introduction of new computer games. Players, in fact, wish to experience playful exchanges with the objects and characters that compose games. To reach this aim, new technologies have come into the play that comprise the use of video cameras and gesture recognition software. The great news is that such types of technologies could be exploited not only while playing at home on a console, but also in public spaces, thus broadening the use of games to new segments of customers. Nonetheless, to the best of our knowledge, neither relevant exemplars of such specific type of games (that can be played in public spaces) have yet emerged, nor extensive measurement studies exist regarding how players enjoy games in public immersive environments (e.g., fairs, museums and exhibits), the motivation being that those technologies that support completely hands-free gaming have been commercialized only very recently. Hence, our contribution with this article is twofold: on one side we want to illustrate the main design principles we have devised to design a gestural game to be played in a public space, based on novel hand following and gesture recognition techniques. On the other side we wish to report on real measurements we took when over one hundred players enjoyed our gestural game at the Shanghai 2010 World Expo.

Augmenting augmented reality with pairwise interactions: The case of Count Luigi Ferdinando Marsili shooting game

“…We discussed on how to augment the interaction degree of AR mobile apps by exploiting interactions occurring between multiple users and virtual objects [11]. We applied such ideas to the design of a game that celebrates the foundation of the Academy of Science of the University of Bologna.…”

A hand gesture recognition technique for human–computer interaction

“…In fact, vision-based approaches may overcome the major problems of the hardware used because they will address the limitations of the device such as restricted motion capture range and carrying an uncomfortable attachment. For example, the results of hand follower algorithms proposed in [30] and [31] can be easily converted to our gesture representation and can be fed to the recognizer machines. It is even possible to extend the usage area of our approach to the public spaces using the hand segmentation and recognition approaches described in [32] that generate hand coordinates, which is sufficient for us to recognize hand gestures.…”