Webpage Saliency

Shen, Chengyao; Zhao, Qi

doi:10.1007/978-3-319-10584-0_3

Cited by 85 publications

(93 citation statements)

References 23 publications

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“…The lack of publicly available datasets on web pages was also highlighted by Shen and Zhao [2014]. We also tried to contact some other researchers in related fields 2 if they have appropriate eye tracking datasets with a sufficient number of users to share with us.…”

Section: Discussionmentioning

confidence: 99%

Eye tracking scanpath analysis on web pages

Eraslan

Yeşi̇lada

Harper

2016

Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research &Amp; Applications

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The number of users required for usability studies has been a controversial issue over 30 years. Some researchers suggest a certain number of users to be included in these studies. However, they do not focus on eye tracking studies for analysing eye movement sequences of users (i.e., scanpaths) on web pages. We investigate the effects of the number of users on scanpath analysis with our algorithm that was designed for identifying the most commonly followed path by multiple users. Our experimental results suggest that it is possible to approximate the same results with a smaller number of users. The results also suggest that more users are required when they serendipitously browse on web pages in comparison with when they search for specific information or items. We observed that we could achieve 75% similarity to the results of 65 users with 27 users for searching tasks and 34 users for browsing tasks. This study guides researchers to determine the ideal number of users for analysing scanpaths on web pages based on their budget and time.

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Section: Discussionmentioning

confidence: 99%

Eye tracking scanpath analysis on web pages

Eraslan

Yeşi̇lada

Harper

2016

Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research &Amp; Applications

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“…To make clear this point, we estimated the joint probability distribution of saccade amplitudes and orientations with fixations collected on webpages (Shen & Zhao, 2014). The main characteristics of the dataset proposed by Shen and Zhao (2014) are given in Table 1.…”

Section: Methodsmentioning

confidence: 99%

Saccadic model of eye movements for free-viewing condition

2015

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In this paper, we propose a new framework to predict visual scanpaths of observers while they freely watch a visual scene. The visual fixations are inferred from bottom-up saliency and several oculomotor biases. Bottom-up saliency is represented by a saliency map whereas the oculomotor biases (saccade amplitudes and saccade orientations) are modeled using public eye tracking datasets. Our experiments show that the simulated scanpaths exhibit similar trends of human eye movements in a free-viewing condition. The generated scanpaths are more similar to human scanpaths than those generated by two existing methods. In addition, we show that computing saliency maps from simulated visual scanpaths allows to outperform existing saliency models.

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“…Figure 1: Sample images from (Shen & Zhao, 2014)'s datasets (Top row) and from (Coutrot & Guyader, 2014b) (Second row presents images from the face category whereas the third row presents images from the landscape category). Table 1 presents the six eye tracking datasets used in this study.…”

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confidence: 99%

“…These first 3 165 datasets are classically used for benchmaking saliency models. (Shen & Zhao, 2014)'s dataset is composed of 146 static webpage images. The last dataset proposed by (Coutrot & Guyader, 2014b) is composed of video clips belonging to two different visual categories: humans having conversations, and landscapes.…”

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confidence: 99%

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Introducing context-dependent and spatially-variant viewing biases in saccadic models

Meur

Coutrot

2016

Vision Research

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Previous research showed the existence of systematic tendencies in viewing behavior during scene exploration. For instance, saccades are known to follow a positively skewed, long-tailed distribution, and to be more frequently initiated in the horizontal or vertical directions. In this study, we hypothesize that these viewing biases are not universal, but are modulated by the semantic visual category of the stimulus. We show that the joint distribution of saccade amplitudes and orientations significantly varies from one visual category to another. These joint distributions are in addition spatially variant within the scene frame. We demonstrate that a saliency model based on this better understanding of viewing behavioral biases and blind to any visual information outperforms well-established saliency models. We also propose a saccadic model that takes into account classical low-level features and spatially-variant and context-dependent viewing biases. This model outperforms state-of-the-art saliency models, and provides scanpaths in close agreement with human behavior. The better description of viewing biases will not only improve current models of visual attention but could also influence many other applications such as the design of human-computer interfaces, patient diagnosis or image/video processing applications.

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Webpage Saliency

Cited by 85 publications

References 23 publications

Eye tracking scanpath analysis on web pages

Eye tracking scanpath analysis on web pages

Saccadic model of eye movements for free-viewing condition

Introducing context-dependent and spatially-variant viewing biases in saccadic models

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