Methodology for conducting an experimental study on the perception of visual information in the field of human peripheral vision

Kheyfits Antonina Evgenievna Assistant, Higher School of Design and Architecture, Peter the Great St. Petersburg Polytechnic University 195251, Russia, Leningradskaya oblast', g. Saint Petersburg, ul. Politekhnicheskaya, 29 antoni.t-h@mail.ru Other publications by this author     Yanchus Viktor Edmundasovich PhD in Technical Science Associate Professor, Higher School of Design and Architecture, Peter the Great St. Petersburg Polytechnic University 195251, Russia, Leningradskaya oblast', g. Saint Petersburg, ul. Politekhnicheskaya, 29 victorimop@mail.ru Other publications by this author

Borevich Ekaterina Vladislavovna Assistant, Higher School of Design and Architecture, Peter the Great St. Petersburg Polytechnic University 195251, Russia, Leningradskaya oblast', g. Saint Petersburg, ul. Politekhnicheskaya, 29 plasma5210@mail.ru Other publications by this author

1. Introduction

The progress of technological means of information processing and visualization makes it possible to automate the workplaces of operators who control the state of complex technical systems with a dynamically changing state. When controlling a dynamic system in real time, the operator is forced to observe an array of simultaneously changing parameters on monitor screens for a long time, which leads to a high degree of fatigue and high mental stress ^[1]. Computer tools allow you to systematize dynamic information about the observed object and present it graphically and in the form of animated diagrams. In contrast to the textual representation of data, the graphical visualization method using infographics offers a more effective approach to the operator's analysis of numerous parametric data on the state of an object ^[2].

However, the use of computer tools in creating control systems leads to the fact that the operator's work moves from a real environment to a virtual environment with its own interface and operating rules. A lot of scientific material has been written about the principles of operator interaction with a computer system, the concept of an immersive environment is introduced ^[3], and fundamentally new methods for analyzing this interaction are proposed. However, it should be noted that the operator's sphere of interaction narrows from a 360-degree space to the size of a monitor (or several monitors) and, accordingly, spatial compression of information occurs in the appropriate proportion. A similar situation occurs when the action moves from the theater stage to the cinema screen. Reading information from the monitor screen is mainly due to central vision. The issue of expanding the reading area of visual information when working with a computer system is poorly understood and requires research.

2. The theoretical model

Let's consider a system for reading information by the human eye. The human eye is able to successfully read information that is within sight of the central fovea, or fovea (2 angular degrees of the visual field), since it is in this area that maximum image clarity is achieved. Information is perceived slightly worse in the upper part (5° on both sides of the fixation point), and everything further than 5° (the periphery) is perceived poorly (Fig. 1). For languages written on the left and alphabetically, this means that we can extract information from three to four letters to the left of the fixation and 14-15 characters (including spaces) to the right of the fixation ^[4,5]. Information perception occurs during fixations (slow movement of the central point of view) (Fig. 2), which range from 150 to 350 milliseconds and depend on the observer's task of perceiving information.

Fig. 1.Areas of vision of the human eye

However, the possibilities of peripheral vision have not been fully explored. The experience of athletes in game sports shows that as a result of training, they develop the ability to perceive significantly large amounts of information with their peripheral vision compared to an untrained person.

Fig. 2. An example of the trajectory of the gaze

When perceiving textual information, the central area of vision is involved, where the image is sharpest ^[6]. The following statement is accepted as the hypothesis of the study: graphic concise images representing color spots of a certain size and perceived by a person as a single image, unlike text, can be perceived in the peripheral area of human vision. The study of this issue will potentially expand the efficiency of the interface and identify information that can be captured by the peripheral field of vision (Fig.1).

3. Experimental setup

Based on the technical capabilities of the SMIRED 250 software and hardware complex ^[7], we define the near peripheral zone of vision as the object of research. In the experimental setup, the distance from the subject to the monitor (Fig. 3) is 60 cm with a monitor size of 64 by 40 cm. The selected sizes and distances determine the maximum viewing angle of the subject, which is plus or minus 30°, it overlaps the near peripheral zone of vision (see Fig.1).

In the experiment being developed, the influence of three factors is investigated: the color, size, and distance of the object from the center of the stimulus. In accordance with the selected factors, the stimulus material of the experiment was developed.:

- the color selection is made in accordance with Goering's theory – black-and-white channel and color channels: red-green, yellow-blue^[8];

- user-readable pictographs/icons have been selected due to the shape for maximum operator convenience ^[9];

- the distance from the point of primary focus of vision in the stimuli was ±15°, ±20°, ±25°, this corresponds to a distance of 300 px, 570 px, 840 px from the center of the monitor.

Fig. 3. The layout of the screen and the one being tested in the experiment

A software module specially developed in the processing language was used to fill the stimuli with pictographs randomly from a set created. A total of 54 incentives were prepared.

To create the stimulus material, it was necessary to create a set of images containing 6 icons arranged in a circle and equidistant from the icon located in the center. A database of 12 pictographs was created (Fig. 4).

Fig. 4. A set of pictographs used in the experiment

In this experiment, icons on different stimuli should be made in different colors: red "r" (ED1E2E), green "g" (019C59), blue "b" (1C68B1), orange "o" (F68522), black "k" (000000), light gray"w" (E0E7F5), the background of the stimuli is gray (B3B5B5). In addition, the icons have different sizes: large "big" 93px, medium "normal" 66px, small "little" 42px.The distance from the center takes three values: Closenearly (Low) – 300px radius, Middle – 570px radius, Farther (high) – 840px radius (Fig.5). An example of the stimulus material is shown in Figure 6.

Fig. 5. The distance of the pictographs from the center of the stimulus. The size of the stimuli is 1920*1080px

Fig.6. An example of the stimulus material

Next, the algorithm for creating stimuli with a given value of the radius of the distance of the icons from the center is shown in Figure 6.

Fig. 6. Block diagram of the algorithm for creating incentive material

At the entrance, we have a database of vector files with svg-type pictographs.,

we create three arrays of icons of the PShape class, in which we set different sizes using the scale (1) function for large icons, scale (0.7) for medium and scale (0.5) for small.

Next, we will create a new class of objects, which we will call Icon, in order to store, in addition to the image itself, information about whether the icon has already been used to stimulate information about the zone in which it will be placed.Create arrays of icons for each size and color (6 colors in total). A total of 18 arrays have been created. There are six zones equidistant from the center to position the icons.

In the experiment, the subject was given the following task: to look at the center of the stimulus, memorize the icon located there, then find an identical icon on a circle outside the center of the stimulus and mark it by hovering the mouse cursor and pressing a button. The coordinates of the computer mouse button click are recorded in the experiment database, after which the transition to the next stimulus takes place.

4. The results of the experiment

The experiment involved 22 people aged 18 to 25 from among the students of Peter the Great St. Petersburg Polytechnic University. 7,930 fixations and 10,720 saccades were collected. Statistical processing of the experimental results was carried out using ANOVA analysis of variance ^[10]. The following parameters of the viewing pattern were analyzed: the time of observation of the stimulus, the average duration of fixations, the average duration of fixations when observing one stimulus, the average number of fixations when observing one stimulus, the average time of saccades and the average number of saccades when observing one stimulus. The objective of the analysis was to identify the influence of the factors of the size of the pictographs, their distance from the center and the color of the diagrams, as well as factors of gender, the presence / absence of artistic training and the type of education (humanitarian - technical). The value of the p-value significance criterion for hypothesis acceptance was 0.05. The p-value values obtained as a result of the computational procedure are presented in Table 1.

Table.1. Calculated p-value values. The values that make it possible to accept the hypothesis about the influence of the factor are highlighted in red.

A graph of the distribution density of the time spent viewing a stimulus, depending on the factors of color, size, distance from the center, presence/absence of artistic training, and gender are shown in Figures 7, 8,9.

7. Graphs of the distribution density of the time spent viewing a stimulus depending on the factors of color (r – red, g – green, b – blue, o – orange, k – black, w – light gray), size and distance.

Figure 8. Graph of the distribution density of the time spent viewing a stimulus, depending on the factors of artistic training (0 – no training, 1 – artistic training), color, and distance from the center.

Fig. 9. Graph of the distribution density of the time spent viewing a stimulus depending on the gender attribute (0 - women, 1 - men), color, and distance from the center.

Based on the results of the statistical analysis, several observations can be made:

1) The parameters of the viewing pattern have a statistically significant dependence on the factors of color, size, and distance of the object from the center of the stimulus.

2) The parameters of the review template have a statistically significant dependence on factors such as education (technical - humanitarian) and gender.

3) The parameters of the viewing pattern have no statistically significant dependence on the factor of artistic training.

4) The above correlations of the parameters of the viewing pattern and the factors changed in the experiment depend on the task being solved by the subject.

It should be noted that in order to conduct a deeper analysis of the issue of human perception of visual information in the field of peripheral vision, it is necessary to increase the number of subjects.

5. Conclusions

As a result of the work done, a methodology has been developed for conducting experimental studies of human perception of visual information in the field of peripheral vision using the AI-tracking software and hardware complex.

The developed technique was tested on 23 subjects from among the students of Peter the Great St. Petersburg Polytechnic University and proved its viability.

The developed technique can be used in conducting research on the perception of visual information in graphical interfaces of remote control systems for dynamic objects.