Can a Clipboard Improve User Interaction and User Experience in Web-Based Image Search?
We investigate if a clipboard as an extension to standard image search improves user interaction and experience. In a task-based summative evaluation with 32 participants, we compare plain Google Image Search against two extensions using a clipboard. One clipboard variant is filled with images based on DCG ranking. In the other variant, the clipboard is filled based on gaze information provided by an eyetracker. We assumed that the eyetracking-based clipboard will significantly outperform the other conditions due to its human-centered filtering of the images. To our surprise, the results show that eyetracking-based clipboard was in almost all tasks worse with respect to user satisfaction. In addition, no significant differences regarding effectiveness and efficiency between the three conditions could be observed.
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- 1.Biedert, R., Buscher, G., Schwarz, S., Möller, M., Dengel, A., Lottermann, T.: The Text 2.0 Framework – Writing Web-Based Gaze-Controlled Realtime Applications Quickly and Easily. In: Proc. International Workshop on Eye Gaze in Intelligent Human Machine Interaction, EGIHMI (2010)Google Scholar
- 5.Hornof, A.J., Cavender, A.: Eyedraw: enabling children with severe motor impairments to draw with their eyes. In: Proc. Conference on Human Factors in Computing Systems, pp. 161–170. ACM (2005)Google Scholar
- 7.Jeff, A.J., Jaimes, R., Pelz, J., Grabowski, T., Babcock, J., Chang, S.-F.: Using human observers’ eye movements in automatic image classifiers. In: Proc. of SPIE Human Vision and Electronic Imaging VI, pp. 373–384 (2001)Google Scholar
- 9.Pasupa, K., Klami, A., Saunders, C.J., Kaski, S., Szedmak, S., Gunn, S.R.: Learning to rank images from eye movements. In: Proc. 12th International Conference on Computer Vision, pp. 2009–2016 (2009)Google Scholar