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User studies are typically difficult, recruiting enough users is often problematic and each experiment takes a considerable amount of time to be completed. In these studies, eye tracking is increasingly used which often increases time, therefore, the lower the number of users required for these studies the better for making these kinds of studies m...
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... and Nielsen (2009) suggest to have 39 users for a stable heat map to highlight which parts of web pages get more attention. However, as shown in Figure 2, these maps do not show eye movement sequences and they are much easier to analyse in comparison with scanpaths. Therefore, we should not assume that this number is also appropriate for scanpath analysis. ...
Context 2
... this study is an important step forward in existing research. Furthermore, the results are still consistent with the suggestions for heat maps (Pernice & Nielsen, 2009), especially for the browsing tasks, even though the analysis of heat maps are much easier in comparison with scanpath analysis (see Figure 2 and Figure 4). ...
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Visual dialog is a challenging vision-language task, which requires the agent to answer multi-round questions about an image. It typically needs to address two major problems: (1) How to answer visually-grounded questions, which is the core challenge in visual question answering (VQA); (2) How to infer the co-reference between questions and the dia...
Visual dialog is a challenging vision-language task, which requires the agent to answer multi-round questions about an image. It typically needs to address two major problems: (1) How to answer visually-grounded questions, which is the core challenge in visual question answering (VQA); (2) How to infer the co-reference between questions and the dia...
Citations
... Table 1 also shows us that these studies mostly rely on small sample sizes (3-97 participants). This is mainly because eye-tracking studies require user participation and it is costly to perform user studies in terms of time and scope [4,26]. However, previous studies show that algorithms can be trained in such a way to cope with such small sample sizes. ...
Eye-tracking studies typically collect enormous amount of data encoding rich information about user be5 haviours and characteristics on the web. Eye-tracking data has been proved to be useful for usability and accessibility 6 testing and for developing adaptive systems. The main objective of our work is to mine eye-tracking data with machine
7 learning algorithms to automatically detect users’ characteristics. In this paper, we focus on exploring different machine 8 learning algorithms to automatically classify whether users are familiar or not with a web page. We present our work 9 with an eye-tracking data of 81 participants on six web pages. Our results show that by using eye-tracking features, we 10 are able to classify whether users are familiar or not with a web page with the best accuracy of approximately 72% for 11 raw data. We also show that with a re-sampling technique this accuracy can be improved more than 10%. This work
12 paves the way for using eye-tracking data for identifying familiar users that can used for different purposes, for example 13 it can be used to better locate certain elements on pages such as adverts to meet the users’ needs or it can be used to 14 do better profiling of users for usability and accessibility assessment of pages.
... Since the number of users required for user studies including eye-tracking studies is a controversial issue over the years, we also investigated the effects of the number of users on the results of the STA algorithm. During our experiments with the combination of the initial and additional datasets, we observed that the STA algorithm could achieve almost the same results with fewer users [20,21]. In particular, we observed the possibility of achieving 75% similarity to the results of 65 users with 27 users for searching tasks and 34 users for browsing tasks. ...
Eye-tracking research enables us to understand how users interact with visual stimuli. It has widely been used to understand user interaction with web pages for various purposes, such as to assess the usability and accessibility of web pages. However, individual eye movement sequences (i.e. scanpaths) tend to be complicated and differ from each other, and therefore the analysis of those sequences is challenging. In our previous work, we propose an algorithm called Scanpath Trend Analysis (STA) that analyses the individual scanpaths of multiple users on a particular web page and identifies their trending path. We also present how STA could be used for autism detection and demonstrate that it works with approximately 60% accuracy regardless of web pages and tasks. In this article, we first summarise STA with its application in autism detection, and then discuss future directions for this research.
... Researchers focus on eye tracking technology in variety of disciplines, such as the medical field [40,41], marketing [42], usability research [43], information technologies [44], agriculture [45], multimedia technology [46,47], education [48,49] and aviation [30,50,51]. Review of human factor research in marine transportation field shows that a limited number of studies have been carried out on eye tracking of ship officers, especially on education and training, considering other related fields such as; the aviation industry. ...
The purpose of this study is to experiment eye tracking in situational awareness assessment in Bridge Resource Management training of ship officers who play a critical role in maritime accidents. The maritime industry focuses on human factor developing and improving regulations including training requirements to prevent marine casualties. The mandatory Bridge Resource Management training as per international regulations includes assessment of situational awareness of trainees in full mission ship bridge simulators. The study involves capturing and analyzing eye movement data from maritime cadets and ship officers with sea experience in a simulation exercise. An eye tracking analysis software and eye tracking glasses are used for the study. Inferential and descriptive analyses were both used to validate the results. Significant differences were found between fixation duration measurements of novice cadets and experienced officers. Heat map visualizations also revealed differences in focuses of attention among participants. The evaluations of the certified simulator assessors are considered as the ground truth, and the results were compared to and discussed accordingly. The results show that the eye tracking technology is a valuable complementary tool for assessment of situational awareness in a simulator environment, utilized with the existing conventional observation and performance measurement methods. The study reveals that eye tracking provides the assessor with novel data in simulator based maritime training, such as focus of attention, which contributes to the evaluation of the situational awareness. The study, therefore, contributes to maritime education aiming to improve the effectiveness of Bridge Resource Management training. It also contributes to scientific research on eye movement in maritime field by proposing the integration of eye tracking in the Bridge Resource Management training.
... We also wanted to compare our approach with the state-of-art approaches. In our previous work, we followed a systematic way to find web page segmentation approaches with publicly available implementation, but we could find only a limited number of those approaches [17]. Not all web page segmentation approaches with publicly available implementation are suitable for comparison. ...
... They also suggest when researchers want to conduct qualitative analysis to gain some insights about how users interact with visual stimuli by watching their eye movements, 6 users would be sufficient for them. Furthermore, Eraslan et al. [15] [17] raised the possibility to achieve 75% similarity to the results of 65 users with 27 users for searching tasks and 34 users for viewing tasks when Scanpath Trend Analysis (STA) is conducted to identify the trending path of multiple users on a web page in terms of its AOIs. The dataset we used to evaluate our approach here was constructed with a higher number of users compared to the suggested number of users. ...
Web pages are composed of different kinds of elements (menus, adverts, etc.). Segmenting pages into their elements has long been important in understanding how people experience those pages and in making those experiences “better.” Many approaches have been proposed that relate the resultant elements with the underlying source code; however, they do not consider users’ interactions. Another group of approaches analyses eye movements of users to discover areas that interest or attract them (i.e., areas of interest or AOIs). Although these approaches consider how users interact with web pages, they do not relate AOIs with the underlying source code. We propose a novel approach that integrates web page and eye tracking data driven approaches for automatic AOI detection. This approach segments an entire web page into its AOIs by considering users’ interactions and relates AOIs with the underlying source code. Based on the Adjusted Rand Index measure, our approach provides the most similar segmentation to the ground-truth segmentation compared to its individual components.
... Researchers focus on eye tracking technology in variety of disciplines, such as the medical field [29] [30], marketing [31], usability research [32], information technologies [33], agriculture [34], multimedia technology [17] [35], education [36] [37], and aviation [38]. Review of human factor researches in marine transportation field shows that a very limited number of studies have been carried out on eye tracking for ship officers. ...
The purpose of this study is to experiment an assessment method using eye tracking technology in simulator based electronic navigation training of ship officers who play a critical role in maritime accidents. The maritime industry focuses on human factor developing and improving regulations, training requirements and technology to prevent marine casualties. The mandatory use of simulations in maritime training as per international regulations includes competency assessment as a vital process. The study involves capturing and analyzing eye movement data from ship officers with sea experience in simulation exercises for assessing competency. A system including an eye tracking analysis software and eye tracking glasses is used for the study. Inferential and descriptive analysis were both used to validate the results. Significant differences were found between electronic navigation competencies of expert and novice ship officers. The results show that the eye tracking technology is a valuable tool for assessment of electronic navigation competency. Comparing novice and expert ship officers’ data proves that eye tracking provides in-depth data which is not obtainable by the available observation methods used in simulation training. The findings show that eye tracking provides the assessor novel data, such as focus of attention, which enables evaluation of the cognitive process and competency. The study, therefore, contributes to maritime education aiming to improve the effectiveness of simulator based maritime training which is vital for maritime safety. It also contributes to scientific research on eye movement in maritime field by proposing the integration of eye tracking in competency assessment in electronic navigation training as a part of simulation based maritime education.
... However, to get the group viewing pattern, we need to take into account all individual scanpaths rather than focus on a single one, like the identified scanpath in Figure 1(b), which we call representative scanpath. The surge of interest in dynamic vis-ual attention gives rise to various methods for representative scanpaths identification, most of which either stem from sequence mining algorithms or target a specific category of visual stimuli such as web pages (Eraslan, Yesilada & Harper, 2014, 2016a, 2016b, 2016c, 2017a, 2017b. So they have limitations when applied to analyze scanpaths. ...
Scanpaths are composed of fixations and saccades. Viewing trends reflected by scanpaths play an important role in scientific studies like saccadic model evaluation and real-life applications like artistic design. Several scanpath synthesis methods have been proposed to obtain a scanpath that is representative of the group viewing trend. But most of them either target a specific category of viewing materials like webpages or leave out some useful information like gaze duration. Our previous work defined the representative scanpath as the barycenter of a group of scanpaths, which actually shows the averaged shape of multiple scanpaths. In this paper, we extend our previous framework to take gaze duration into account, obtaining representative scanpaths that describe not only attention distribution and shift but also attention span. The extended framework consists of three steps: Eye-gaze data preprocessing, scanpath aggregation and gaze duration analysis. Experiments demonstrate that the framework can well serve the purpose of mining viewing patterns and “barycenter” based representative scanpaths can better characterize the pattern.
... Eye tracking studies are increasingly used for understanding how people interact with web pages [1]. However, these studies are typically costly and time-consuming [2,3,4]. Some of the main reasons are the difficulty in finding participants, the cost of equipment and the need for a separate session for each participant. ...
... We have focussed on the academic papers published in the Journal of Eye Movement Research (JEMR) 3 and the Proceedings of ACM Symposium on Eye Tracking Research & Applications (ETRA) 4 as these are main venues for publication on eye tracking research. After analysing these sources in depth, we have found 20 relevant academic papers (9 journal articles [6,11,12,13,14,15,16,3,17] + 11 conference papers [18,19,20,21,22,23,24,25,26,7,2]). These papers show that different kinds of eye tracking studies have been conducted on web pages. ...
... The study was then replicated with other 41 participants to further evaluate the algorithm and investigate the effects of the number of participants on the algorithm [2,3,31]. Therefore, a large amount of eye tracking data was collected with 81 participants. ...
Eye tracking studies are increasingly used for understanding how people interact with web pages. However, these studies are typically costly and time-consuming. Some of the main reasons are the difficulty in finding participants, the cost of equipment and the need for a separate session for each participant. Due to these reasons, eye tracking studies are typically conducted with a small number of users. Therefore, the statistical analysis of the collected data tends to be underpowered which possibly causes a failure to detect a significant difference (Type II Error). One of the solutions for this problem is to allow researchers to crowdsource eye tracking data from other researchers and combine them in an appropriate way to have a large amount of data for their studies, if possible. In this paper, we propose a methodology for creating a corpus of eye tracking data on web pages. This corpus will facilitate crowdsourcing eye tracking data collected on web pages.
In television broadcasts, important information is often conveyed with short inscriptions. In such elements, the typeface, letter case, positioning, timing and colour combinations may affect the speed of information processing to the level of recognition. It is therefore necessary to choose an appropriate combination of these properties. In the present study, we were especially interested in the effects of applied colours in connection with the above-mentioned factors. The speed of recognising three-letter words was measured in different experimental conditions where the typeface of the inscription, its position and colour combination varied. Two typefaces (i.e. Calibri and Georgia), two letter cases (i.e. upper-case and lower-case), two positions (i.e. upper left and right) and four colour combinations (i.e. white on blue, blue on white, white on red and red on white) were tested. The results showed that colour combinations affected the speed of word processing to the level of recognition.
