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In this paper, we propose a new method for comparing scanpaths in a bottom-up approach, and a test of the scanpath theory. To do so, we conducted a laboratory experiment in which 113 participants were invited to accomplish a set of tasks on two different websites. For each site, they had to perform two tasks that had to be repeated ounce. The data were analyzed using a procedure similar to the one used by Duchowski et al. [8]. The first step was to automatically identify, then label, AOIs with the mean-shift clustering procedure [19]. Then, scanpaths were compared two by two with a modified version of the string-edit method, which take into account the order of AOIs visualizations [2]. Our results show that scanpaths variability between tasks but within participants seems to be lower than the variability within task for a given participant. In other words participants seem to be more coherent when they perform different tasks, than when they repeat the same tasks. In addition, participants view more of the same AOI when they perform a different task on the same Web page than when they repeated the same task. These results are quite different from what predicts the scanpath theory.

No abstract

To understand the visual behaviors of people searching for information on Web pages, heatmaps and Areas Of Interest (AOI) are generally used. These two techniques bring interesting information on how Web pages are scanned by several users. However, two remarks can be expressed: the first one relates to the fact that heatmaps are usually used to represent fixation areas for a given task after it is completed. Thus, it does not represent fixation areas over time. The second remark relates to the use of AOI, which must be defined by the analyst. We present a method, which address these two points. This bottom-up approach is based on a mean-shift clustering procedure for the identification of areas of interest, which takes into account the temporal aspect. The identification of AOI is thus data driven. This approach allows us to show the evolution of a posteriori AOI both in space and time. The limitations and implications of this new approach are discussed