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When camera phones are used as magic lenses in handheld augmented reality applications involving wall maps or posters, pointing can be divided into two phases: (1) an initial coarse physical pointing phase, in which the target can be directly observed on the background surface, and (2) a fine-control virtual pointing phase, in which the target can only be observed through the device display. In two studies, we show that performance cannot be adequately modeled with standard Fitts’ law, but can be adequately modeled with a two-component modification. We chart the performance space and analyze users’ target acquisition strategies in varying conditions. Moreover, we show that the standard Fitts’ law model does hold for dynamic peephole pointing where there is no guiding background surface and hence the physical pointing component of the extended model is not needed. Finally, implications for the design of magic lens interfaces are considered.

Abstract — Virtual reality systems often co-locate the display and input (motor) spaces. Many input devices, such as the mouse, use indirect input mappings, and are disjoint from the display space. A study of visual/motor co-location was conducted to determine if there is any benefit to working directly “in ” a virtual environment. Using a fish-tank VR setup, participants performed a 3D object movement task. This required moving an object from the centre of the environment to target regions, using a tracked pen, in both co-located and disjoint display/input conditions. Results were analyzed in the context of Fitts ’ Law, which models rapid aimed movements. Ultimately, no significant differences were found between co-located and disjoint conditions. However, when analyzing object movement in specific directions, the colocated condition was somewhat better than the disjoint one. In particular, movement into the scene was faster when the display and input device were co-located rather than disjoint. Keywords-component; Co-located input and display, virtual hand, human-computer interaction, 3D user interfaces. I.

We present three experiments that systematically examine pointing tasks in fish tank VR using the ISO 9241-9 standard. All experiments used a tracked stylus for a both direct touch and raybased technique. Mouse-based techniques were also studied. Our goal was to investigate means of comparing 2D and 3D pointing techniques. The first experiment used a 2D task constrained to the display surface, allowing direct validation against other 2D studies. The second experiment used targets stereoscopically presented above and parallel to the display, i.e., the same task, but without tactile feedback afforded by the screen. The third experiment used targets varying in all three dimensions. Results of these studies suggest that the conventional 2D formulation of Fitts ’ law works well for planar pointing tasks even without tactile feedback, and with stereo display. Fully 3D motions using the ray and mouse based techniques are less well modeled.

The study of Human Computer Interaction improves the usability and functionality of computers to the user’s needs. The purpose is to make computers as effective and efficient as possible. Below our team analyzed the Multi-Cultural Greek Council (MGC) website in order to see if they are using their resources to their optimal potential. We found through task analyses, graphical analysis, as well as a mouse location identifier the website in its current form has areas of improvement. As you continue, you will find the recommendations provided in order to improve the overall design of the website. 2 Table of Contents

The nervous system controls the behavior of complex kinematically redundant biomechanical systems. How it computes appropriate commands to generate movements is unknown. Here we propose a model based on the assumption that the nervous system: 1. processes static (e.g. gravitational) and dynamic (e.g. inertial) forces separately; 2. calculates appropriate dynamic controls to master the dynamic forces and progress toward the goal according to principles of optimal feedback control; 3. uses the size of the dynamic commands (effort) as an optimality criterion; 4. can specify movement duration from a given level of effort. The model was used to control kinematic chains with 2, 4 and 7 degrees of freedom (planar shoulder/elbow, 3D shoulder/elbow, 3D shoulder/elbow/wrist) actuated by pairs of antagonist muscles. The muscles were modeled as second-order nonlinear filters and received the dynamics commands as inputs. Simulations showed that the model can quantitatively reproduce characteristic features of pointing and grasping movements in three-dimensional space, i.e. trajectory, velocity profile, final posture, … Furthermore, it accounted for amplitude/duration scaling

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This is the preprint version of the following article: Michalski R., Grobelny J., Karwowski W. (2006). The effects of graphical interface design characteristics on human-computer interaction task efficiency. International Journal of Industrial Ergonomics, 36, 959-977. doi: 10.1016/j.ergon.2006.06.013 The preprint html version is also available at:

This is the preprint version of the following article: Michalski R., Grobelny J. (2008). The role of colour preattentive processing in human-computer