MarkerMouse: Mouse Cursor Control Using a Head-Mounted Marker

Abstract. We propose MarkerMouse, an inexpensive method for controlling the mouse cursor using a web cam and a marker placed on the user’s forehead. Two modes of cursor control were compared: position-control and velocitycontrol. In position-control mode the cursor is positioned where the user's head is pointing. In velocity-control mode the mouse cursor moves in a constant speed in the direction the user’s head is pointing. In an experiment designed according to ISO 9241-9, we found a mean throughput 1.61 bps in positioncontrol mode. Throughput was 34 % less, or 1.07 bps, in velocity-control mode. We explain how from the marker image we control the mouse cursor position and reduce noise in our computations

KLM Form Analyzer: automated evaluation of web form filling tasks using human performance models

Abstract. Filling forms is a common and frequent task in web interaction. Therefore, designing web forms that enhance users ’ efficiency is an important task. This paper presents a tool entitled KLM Form Analyzer (KLM-FA) that enables effortless predictions of execution times of web form filling tasks. To this end, the tool employs established models of human performance, namely the Keystroke Level Model and optionally the Fitts ’ law. KLM-FA can support various evaluation scenarios, both in a formative and summative context, and according to different interaction strategies or modeled users ’ characteristics. A study investigated the accuracy of KLM-FA predictions by comparing them to participants ’ execution times for six form filling tasks in popular social networking websites. The tool produced highly accurate predictions (89.1% agreement with user data) in an efficient manner

Selection-Based Mid-Air Text Entry on Large Displays

Abstract. Most text entry methods require users to have physical devices within reach. In many contexts of use, such as around large displays where users need to move freely, device-dependent methods are ill suited. We explore how selection-based text entry methods may be adapted for use in mid-air. Initially, we analyze the design space for text entry in mid-air, focusing on singlecharacter input with one hand. We propose three text entry methods: H4 Mid-Air (an adaptation of a game controller-based method by MacKenzie et al. [21]), MultiTap (a mid-air variant of a mobile phone text entry method), and Projected QWERTY (a mid-air variant of the QWERTY keyboard). After six sessions, participants reached an average of 13.2 words per minute (WPM) with the most successful method, Projected QWERTY. Users rated this method highest on satisfaction and it resulted in the least physical movement