Jarmo Kauko

Proximal and distal selection of widgets: designing distributed UI for mobile interaction with large display

A smartphone having touchscreen and short-range networking facilities makes efficient remote control for a large display. In this paper, we report on the results of a case study examining the user performance of Proximal Selection (PS) and Distal Selection (DS) of remote control widgets. DS uses a mobile pointer to zoom-in the region of interest and select the widgets on the large display. PS involves pointing at the large display to transfer the zoom-in view of the pointed region onto the mobile touchscreen and make selections thereafter. The experimental results indicate that PS outperforms DS in terms of speed and user satisfaction with physical effort involved especially in complex tasks requiring multiple widget selection. DS was found to be favorable for simple tasks as it has lower error rate and it does not require attention switch between the mobile and the large display.

Gravity sphere: gestural audio-tactile interface for mobile music exploration

Current solutions for managing music in mobile contexts are inconvenient as they require considerable effort and visual attention. We describe a novel system for exploring music and generating playlists in mobile contexts, and present findings from our formative usability evaluations. The system provides audio-tactile feedback and is controlled by manipulating a devices orientation. The system plays songs associated with the current orientation. A spatial gesture or other command is then used to lock the orientation into a playlist. We evaluated two iterations of a prototype of the system and found that users were successful in exploring music and generating playlists with the system. We found that certain orientations are more common than others. Also, manipulating the prototype felt more natural while walking than sitting. Personalization of the music mapping was requested by users and seen as beneficial for usability.

In class adoption of multimedia mobile phones by gender - results from a field study

In this paper we share our findings from a field study conducted in Panama, focusing on adoption of mobile phones in classroom settings. Our initial findings reveal that during the initial phase of use, boys adopt mobile phone usage faster and explore more functionality; while girls take more time to familiarize themselves with the phones. Girls seem to maintain a better focus on the learning activities using the mobile phones across all tasks. When the task implies an active role then boys also showed high concentration. The videos recorded by the children as part of the learning activities showed a remarkable difference in roles between girls and boys. These findings suggest that it is important to consider the different adoption and exploration strategies of girls and boys with new technologies when designing tools for mobile learning.

Selecting targets on large display with mobile pointer and touchscreen

We present an empirical study that compares Zoom&Pick (ZP) and Semantic Snarfing (SS) which are techniques for selecting targets on a large display using a mobile device. ZP uses a mobile pointer to zoom-in the region of interest and select the targets on the large display. SS involves pointing at the large display to transfer the zoom-in view of the pointed region onto the mobile touchscreen and make selections thereafter. The experimental results indicate that SS outperforms ZP in terms of speed.

Bidirectional pose estimation

This paper presents a method for relative pose estimation between two devices. Typically pose estimation is based on detecting positions of known feature points of a tracked object. I literally take a new viewpoint to this problem by considering two camera-enabled devices tracking each other. The method requires only two feature points, which can be unobtrusively integrated to small, portable devices such as mobile phones. Both devices detect each others feature points and share the positions over a wireless network connection. The combined position data can then be used to calculate the six degrees of freedom (DOF) transformation between the devices. I compared the pose estimation accuracy with a conventional method using a simulation and a real world experiment. The results show that the bidirectional method is significantly more accurate and robust to noise. It is also less affected by the target distance.