Future Work

There are several areas into which this research could expand. The two main areas for expansion are in the enhancement of the head tracking tool and in the evaluation and test design. The test design has many options for enhancement. An automated way to calculate the accuracy could enhance the accuracy data and might provide some more specific insights on the different ways a user may make a mistake and correction with the different input methods. The idea for another interesting study that could be performed came from one of the users who mentioned that they felt their video game experience helped them perform better with both the head tracking and the mouse. Additionally, one user was a retired fighter pilot who had experience with missile targeting systems that used head gaze for targeting; this user mentioned that the head tracking felt natural. It would be interesting to design an experiment in which head tracking was used to navigate a video game or flight simulator space and compare it to the other methods of input common in that domain. Additionally, repeating the experiment with users who had similar levels of experience with the mouse and the head tracking would be interesting, to see if the head tracking would outperform the mouse or at least be comparable. The hard part of doing that would be finding users with so little experience with the mouse, since it is far and away the dominant method of input for computing. Finally, a simple

improvement to the test design would be to create a standard questionnaire for users to fill out after completion of the various tasks as this would be helpful in making the qualitative data easier to compare across users.

Some improvements to the tool itself would be worthwhile towards enhancing performance compared to the other input methods. Since the focus of this research was to evaluate the concept of head tracking as a method of panning spatial data, the

algorithm chosen for the actual tracking was a compromise of acceptable performance and easier implementation. Improving the performance of the head tracking, both in different lighting conditions and in response time would be helpful. Additionally, creating a more automated way of training the system, perhaps one that can handle users in different starting positions would go a long way toward enhancing the user perception of the system. Adding in other dimensions of control, such as zooming with a blink, could provide a path for the tool to become more useful and practical for everyday use. Finally, it is hard for the user to get the panning via head tracking to stop exactly where they want it to, so the tracking and response to small movements could use some refinement. Some combination of these enhancements would most likely improve the results of this research.

Extending the tool to explore how well head tracking would work in a 3D

environment, particularly in light of the demonstrated ease of use in the 2D environment, would also be a worthwhile endeavor.

9. Conclusion

This research set out to examine and evaluate the performance of head tracking as an input method for panning 2D spatial information. This is an important step toward removing the need for a user to occupy their hands with navigating through information, either to enable disabled users or to enhance the capabilities of a typical user by allowing them to use their hands for other tasks while navigation is completed with natural

motions like using head turn for control.

This evaluation was completed in two parts. The first part was to create the head tracking application. This application was created using Adobe Flex, Actionscript, and the Google Maps API. It was created such that it is operating system independent and has a low cost to use, only requiring an internet connection, a standard webcam, and the Adobe Flash player. The second part consisted of 20 users completing five tasks of increasing complexity with three input methods: mouse, laptop touchpad, and the head tracking application. Each task was timed and an accuracy rank was assigned to each input method for each task. The results proved to be statistically significant using a one- way, within-subject ANOVA and revealed that the head-tracking was slightly behind the mouse in performance, but significantly ahead of the touchpad.

This paper concludes that, as a method of input, head tracking provides intuitive and precise control for panning two-dimensional spatial data. With further application refinement and user practice, head tracking may ultimately outperform the mouse in navigating spatial information.

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