Motion Detection as Interaction Technique for Games & Applications on Mobile Devices

Mobile devices become smaller and more powerful with each generation distributed. Because of the tiny enclosures the interaction with such devices offers limited input capabilities. In contrast there are hardly any mobile phones purchasable that do not have a built-in camera. We developed a concept of an intuitive interaction technique using optical inertial tracking on mobile phones. The key of this concept is the user moving the mobile device which results in a moving video stream of the camera. The direction of the movement can be calculated with a suitable algorithm. This paper outlines the algorithm Projection Shift Analysis developed to run on mobile phones. 1. MOTIVATION Our approach detects the relative motion of the camera in the two-dimensional pixel space of the image. As camera movement directly results in motion of all scene components the motion of the camera movement can be defined as the inverse movement of the scene. If there are no significant scene components moving for itself conventional motion detection methods can be used to analyse the video stream. There are several algorithms from different fields of computer graphics and image processing used to parameterise the motion of the scene. Although they pursue different approaches, all of them would analyse the scene motion sufficiently. Due to low CPU and memory resources on mobile phones we developed the Projection Shift Analysis algorithm for motion analysis. There is a wide range of applications for the motion parameter, for example controlling a game similar to joystick interaction. Another possible application could interpret motion gestures or control the cursor like the stylus input technique on PDAs. 2. RELATED WORK In [8] Geiger et al. present concepts for mobile games and address interaction issues concerning mobile devices. The simplest approach to track objects is detecting significant features in an image, e.g. edges. Naturally, edge detection methods like the Robert, Prewitt, Sobel, Laplace or Canny [2] filters are used to achieve this. Motion Detection in 3D-Computer Graphics, Mixedand Augmented Reality is often referred to as Tracking. Beier et al. presented a markerless tracking system using edge detection in [1]. Comport et al. propose a robust markerless tracking system in [3]. A specialised solution to the problem of markerless tracking was published by Simon et al. in [15]. In [11] Moehring et al. present a marker-based tracking system designed especially for mobile phones. Kato and Billinghurst developed the optical marker based tracking system ARToolKit published in [9]. Foxlin et al. present a wide spectrum of optical inertial tracking systems in [5, 6, 17]. Additionally, a taxonomy of Motion Detection methods has been published in [4]. In [10] Koller presents a method to track the position of cars using an optical system. Siemens Mobile developed a game called Mozzies, that is distributed with the mobile phone SX1 by default. This Symbian based game augments the background video from the camera with moths. The user can point the gun at a moth and shoot it by moving the phone and pressing the appropriate button. In [7] Geiger et al. present an interesting approach of an augmented reality version of a soccer game running on a PDA. 3. INTERACTION TECHNIQUES This chapter describes and classifies various interaction techniques used on mobile devices nowadays. There are a few main parameters that define the usability of those techniques. The reaction time between the user input and the response on output devices such as the display is a very crucial parameter. Any visual response on the output device after about 200 ms is not interpreted as a direct reaction to the user, but as a separate event. The quantity of actions a user is able to perform using a specific input technique defines the speed at which he can interact with the device. The intuitivity of an input method strongly affects the usability