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Conspicuity in realistic scenes: an eye-movement measure
Applied Ergonomics 1989, 20.4,267-273
Conspicuity in realistic scenes: an e y e - m o v e m e n t measure T. Boersema*, H.J.G. Zwaga t and A.S. Adams** *Department of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands tDepartment of Social Sciences, University of Utrecht, The Netherlands **School of Psychology, University of New South Wales, Australia An experiment is described to measure the distracting effects of advertisements on the conspicuity of routing signs in realistic scenes. Slides of railway station scenes were shown in which subjects had to search for a target word used in a routing sign present in the scene. Eye movements were recorded to determine search time and number of fixations during search time. Both search time and number of fixations increased systematically with the number of advertisements in two of the three experimental scenes. The distribution of fixations over the scenes is discussed. Keywords: Eye movement, route information, signs, conspicuity
Introduction In the presentation of routing information such as is found in airport terminals, railway stations and shopping centres, many questions remain unanswered concerning practical methods of ensuring the conspicuity of that information. The relative conspicuity of an object in this situation can be operationally defined in terms of the probability that the object will be noticed by an observer within a fixed time or, conversely, in terms of the time required to locate the object. While conspicuity is determined by many properties of the object itself, and by the cognitive state of the observer, the question addressed here concerns the distracting effect of surrounding advertisements, which themselves are, of course, designed to be conspicuous. Early laboratory work on searching for targets in cluttered visual fields showed that giving information about the physical properties of a target greatly assisted a search task (Green and Anderson, 1956; Smith, 1962; Williams, 1966). More recent studies led to the conclusion that the greater the degree of physical difference between target and background items, the smaller the slope of the curve relating detection time to number of background items (Francolini and Egeth, 1979; Treisman and Gelade, 1980). Kr6se (1986) showed that a positive correlation existed between the detectability of a target and the structure dissimilarity between target and background items. In examining separate dimensions in detail, Jenkins and Cole (1982) found that background density of a field of discs affected a contrast detection task but not a size one, while Cole and Jenkins (1984) found that variability of size of the same background discs affected a size detection task but not a contrast one. Yreisman and Gelade (1980) showed that, when a simple detection operation was required, the colour dimension was particularly potent in making a target impervious to the effects of background details. Other studieg have examined these effects in practical contexts. Holahan et al (1978), in a laboratory examination of the effect of distractions around a stop sign, found that
the number, colour and proximity of distractors all had an effect on the reaction time to the sign. Shoptaugh and Whitaker (1984) found that directional traffic signs embedded in photographed street scenes were responded to more slowly when they were embedded in scenes which were rated as being more complex. Cole and Hughes (1984) introduced the concepts of search conspicuity and attention conspicuity in a field study of target visibility. Search conspicuity is the property enabling a target to be seen when it is the object of specific search, whereas attention conspicuity enables an object to be seen when it is unexpected. In their study, subjects drove through streets reporting either specific planted targets, in which case the targets required search conspicuity, or all objects, including these targets, in which case the targets required attention conspicuity. It was found that objects were located least often in the clutter of shopping areas, more often in arterial road sections, and most often in residential road sections. With respect to freeway routing signs, Gordon (1981) found that photographs of such overhead signs were not responded to any more quickly when adjacent irrelevant signs were removed. However, the signs used in Gordon's study were such that their location was highly predictable. Furthermore, the distracting information was, in four out of five signs, in the periphery of the bank of signs to which subjects were attending, and would therefore not be expected to interfere with the task. When searching for routing information in public situations the target location is, of course, not known. In addition, in such situations it is not unusual for advertising signs to be mixed with relevant routing signs. A further complication might be that users new to the environment do not know the shape and the colour of the routing signs. Also, they do not know the precise nature of the routing information (e g, a word, a phrase or a symbol). It is difficult to argue that, in a situation where a user does not know the location, the shape and the colour of the routing signs, nor the nature of the information needed, task performance depends on search conspicuity only. In those circumstances
0003-6870/89/04 0267-07 ~;03.00 © 1989 Butterworth & Co (Publishers) Ltd
Applied Ergonomics
December 1989
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considerable attention conspicuity will be required, at least from the routing signs themselves. To a certain extent search conspicuity will also play a role because users have general expectations about routing systems based on prior experience. Taking these aspects into account, the answer to the practical question as to whether advertisements commonly found in the vicinity of routing signs seriously disrupt the search process cannot be readily predicted from the studies described above. Studying directly the effect of the presence of advertisements on the conspicuity of routing information, Boersema and Zwaga (1985) used slides of railway station scenes containing varying numbers of advertisements of different sizes. Exposure time of the scene slides was one second. The subject's task was tO report the presence of white-on-blue routing signs and then to report each sign's location. These locations had to be indicated on a grid of 24 numbered squares projected after each scene slide. The results of experiment showed that the introduction of only one advertisement in a scene had a greater effect than the further introduction of a second and a third advertisement. The results also indicated that larger advertisements had a greater effect than smaller advertisements. Scoring problems arose when subjects did not correctly identify the grid position for a sign. In those cases a laborious procedure was required in order to keep the objectivity of the scoring at an acceptable level. To avoid these problems and yet maintain the essence of the subject's task (searching for routing information in a realistic scene), the use of reaction time seemed a promising approach. Dewar et al (1976) demonstrated a high correlation between a laboratory measure of reaction time to identify and classify signs and a field measure of legibility. In another study, Dewar et al (1977) showed that laboratory measures of the time required to interpret road direction signs was positively related to data from field traffic flow and driver interview measures. Prior to the experiment reported here, a series of pilot experiments has been conducted by us in which reaction time was used as a performance measure. In these experiments, a slide containing a single-word destination and subsequently a slide showing a scene in a public building were presented to the subjects. They then had to press a button as soon as they had found the sign with the destination in the scene slide. Pressing the button made the slide disappear, and, as a check, the subject had to report the orientation of the arrow associated with the destination (left, ahead or right). Using the same photographic technique as in our previous study (Boersema and Zwaga, 1985), the number of advertisements in three of the scenes shown to the subjects was varied systematically. It was expected that reaction time for a scene (i e, the time needed to find the destination specified, to identify the orientation of the arrow, and to press the button) would increase with the number of advertisements in that scene. However, the reaction time was not systematically related to the number of advertisements in a scene. It can be argued that, in an experiment as has just been described, the reaction time consists of two parts: the time a subject needs to find the routing sign with the target destination (search time) and the time used for reading this routing sign and deciding on the response (processing time). For the purposes of the present investigation into conspicuity,it is only the first of these times which is required. A
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method which eliminates the second of these measures would theretore be preferable as it would remove an unnecessary source of error variance. The use of eye-movement measurement is one such method and is feasible in this case as the times recorded in the reaction time experiment (between one and three seconds) were such that several eye movements would have been executed. An experiment is reported here in which reaction time is divided into search time and processing time by means of eye-movement recording. Subjects have to search for specific destinations in realistic scenes containing varying numbers of advertisements. It is hypothesised that search time will increase systematically with the number of advertisements, even if they are evidently distinct from routing signs, and that processing time and total reaction time will not change significantly. In essence, it can be assumed that the expected increase in search time is the direct effect of changes in the scan path of the subjects resulting from the introduction of advertisements in a scene. This assumption is supported by Kr6se's (1986) eye-movement experiment in which he measured the effect of strong and weak distractors on the locating performance tbr a target. His results showed that the presence of distractors in the visual field increased the number of fixations necessary to locate the target. These extra fixations were located on, or in the direction of, the distractors. It is therefore hypothesised that the introduction of advertisements will increase the number of fixations during search time, with the extra fixations being on the advertisements.
Method Subjects Subjects were 54 undergraduates and staff of the Delft department, aged between 18 and 43 years. All subjects had at least normal, uncorrected vision. The students were paid for their participation.
Stimulus material In the experiment, a total of 15 colour slides showing scenes in railway stations and other public environments were used as stimulus material. All scenes contained routing signs with white lettering on a blue rectangle. Six of the slides were filler slides and showed randomly chosen scenes containing advertisements as welt as routing information. The other nine slides were experimental slides. They were based on original slides from three different scenes (Experimental Scenes A, B and C). From each of these original slides, using photographic techniques, three experimental slides were constructed, containing either zero, one or three advertisements. The advertisements were selected from those encountered in public environments. All advertisements were rectangular, and none contained the routing sign colour of blue. Fig. 1 shows prints of the three experimental slides from Scene A. The scene in Fig. 1 is representative of the other experimental scenes with regard to complexity, transparency, crowdedness, etc. In the experimental scenes, the advertisements were two to three times the size of a routing sign, which is smaller than advertisements normally encountered in those circumstances. In general, the arrangements of routing signs and advertisements in Scenes A, B and C were comparable.
=
E
o~
=
(a)
~;i~i~ ~ <<~
(b) Fig. 1
The three experimental slides from Scene A with zero (a), one (b), and three (c, overleaf) advertisements (see also the front cover for Figs. la and lc)
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(c) In addition to the scene slides, there were 10 other slides: one with a fixation cross and nine slides each with a singleword destination, one for each scene.
tended visual angles between 6.3 ° and 11.7 ° (horizontally) and between 2-6 ° and 6-3 ° (vertically).
Oesign Apparatus Two Kodak Carousel slide projectors, controlled by a PDP 11/73 minicomputer, were used: one to present the fixation cross slide, the other to present the text slides and the associated scene slides. The computer also measured the reaction times. Eye movements were recorded with an eye marker (Demel Debie 84) using the corneal reflection bright pupil technique, The subjects were not allowed to make head movements. The accuracy o f the measurements was one degree; sampling frequency was 50 Hz.
Projection conditions The size of the projected scenes and the distance between subject and projection screen were chosen such that the visual angle of objects in the projected scene was the same as in the actual scene. This means that the subjects in the experiment perceived the projected scene as if they stood in the position o f the camera in the actual scene. Given the picture angle o f the camera lens used, this required that projection width and viewing distance were the same (in the experiment: 200 era; projection height was 132 cmo). Thus, the projected scenes subtended visual angles of 53.1 (horizontally) and 36-5 ° (vertically). The visual angles of the routing signs in the experimental scenes varied between 5-2 ° and 6"9° (horizontally) and between 2 ~9° and 2"9 ° (vertically). The advertisements sub-
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There were three experimental conditions, one for each number of advertisements in the experimental scenes (zero, one or three). Subjects were randomly assigned to three groups o f 18 with each group assigned to one condition. The between-group manipulation was therefore the number of distracting advertisements. The series of filler slides was shown to all subjects in the same order. Depending on the condition, appropriate experimental slides were inserted, with a fixed position for each experimental scene.
Procedure and experimental design Each subject was presented with a total o f nine trials, of which three were the experbnental trials. The nine trials were preceded by six practice trials. Also, for the practice trials, slides showing scenes in public environments were used. Each trial consisted of a sequential presentation o f three slides: a target destination slide, a slide with a fixation cross. and a scene slide. The trial began with the subject pressing a button to start the projection of the target destination, which the subject was instructed to read aloud. This destination was the word to be searched for in the following scene slide. The subject then pressed the button again, and the destination was replaced with a fixation cross, which was followed automatically two seconds later with the scene slide. The subject was instructed to find as quickly as possible both the target destination and its associated
arrow in the scene's routing information, then to press the button to terminate the presentation of the scene slide, and finally to report verbally the direction of the arrow.
depending on condition and scene. In the other cases the eye movement data were incomplete and had to be discarded.
Prior to the analysis of the data from the experimental scenes, the results from the filler scenes for the three independent groups were compared. These data showed no significant differences between the groups on any of the four dependent variables: search time, processing time, reaction time and number of fixations. Subjects made no mistakes reporting the arrow directions.
The results of Scenes A, B and C are presented in Table 1. In this table median times and numbers are given in order to convey an impression of the absolute level of the measurements. The calculations for Meddis's tests, however, are based on mean ranks, so the sometimes minimal differences between medians can be misleading when interpreting the meaning of those differences. Analysis of the time data shows that in Scenes A and C, search times increase systematically with the number of advertisements (0 < 1 < 3, test for trends), while processing times as well as reaction times remain constant (non-specific test). In Scene B there is not only, as for the two other scenes, no effect of advertise ments on processing time and reaction time, but there is also no effect on search time (non-specific test). Analysis of the fixation data shows that in Scenes A and C the number of fixations increases systematically with the number of advertisements (0 < 1 < 3, test for trends). In Scene B there is no effect of advertisements on the number of fixations (nonspecific test).
For each of the three experimental scenes, results and statistical analyses are presented separately because of the uncontrolled qualitative differences between the scenes. The data are analysed using the non-parametric technique developed by Meddis (1984). Meddis's specific test for trends is used to test if search time and number of fixations increase systematically with the number of advertisements. Meddis's non-specific test is used where no direction of an effect was predicted (processing time and reaction time). Complete data were collected from 1 2 - 1 6 subjects,
In order to test the hypothesis that the extra fixations will fall on advertisements, the number of fixations on the advertisements are compared with the number of fixations on the corresponding areas of the scenes ~-here no advertisements are inserted (Table 2). In Condition 1 there is only one fixation on the advertisement (Scene C), and none on the corresponding areas in Condition 0. The numbers of fixations on advertisements in Condition 3 are substantial, whereas the numbers of fixations on the corresponding areas in Condition 0 are again minimal.
Eye movements of the left eye and reaction times were recorded. Search time was operationally defined as the time from the start of the presentation of a scene slide until the beginning of the first fixation on the routing sign. Processing time was the difference between reaction time and search time. Fixations were defined using simultaneously two criteria: one for the duration (at least 60 ms) and one for the maximum acceptable displacement of the line of sight.
Results
Table 1: Median search times (st), processing times (pt) and reaction times (rt)
in seconds and median numbers of fixations during search time (fix) for Scenes A, B and C under Conditions 0, 1 and 3. The numbers of subjects with complete data (n) and the statistical test results are indicated n
st
pt
rt
fix
12 15 14
0"570 0'860 1 '025 Z=2"486 p<0'01
1 "535 1 '500 1 '355 H=0"110 p>0"10
2"005 2"290 2"625 H=4'252 p>0"10
20 3 "0 4"0 Z=3"768 p<0'01
16
0"505
0"820
1 "315
2"0
1
14
0"495
0"955
1 "465
20
3 Key statistic
15
0"570 H=0"300
0"810 H=0"766
1 "390 H=0"182
2"0 H=0"590
p>0"10
p>0"10
p>0"10
p>0'10
16 15
0"530 0"700
1 "520 1 '610
2"225 2"310
2"0 3"0
15
0"710 Z=3"403 p<0'01
2'300 H=2"924 p>0"10
3"020 H=4-458 p>010
3"0 Z=2-384 p <0"01
Scene A Condition 0 1 3 Key statistic
Scene B Condition 0
Scene C Condition 0 1 3 Key statistic
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271
Table 2: Numbers of fixations during the search for Scenes A, B and C on the advertisement under Condition 1 and on the corresponding area under Condition 0 and on the three advertisements under Condition 3 and on the three corresponding areas under Condition 0
One advertisement area Total
Mean per subject
Condition 0
0
0'00
Condition 0
1
0"08
1
0
0'00
3
16
1 "14
Condition 0
0
0"00
Condition0
1
0"06
1
0
0"00
3
5
0"33
Condition 0
0
0"00
Condition 0
0
0"00
1
1
0"07
3
14
0"93
Scene A
Mean per subject
Scene B
Scene C
Scene C
A further exploratory analysis of the data with regard to the duration of fixations and the length of saccades shows no systematic effects. Discussion
The results of the experiment show that the presence of advertisements in an environment can decrease the efficiency with which information can be found. Search time for relevant information increases due to the increase in the number of fixations during search. The analyses of the search time data for Scenes A and C confirm the hypothesis that search time increases systematically with the number of advertisements. The hypothesis that processing time and reaction time will not change is confirmed for all three experimental scenes. The results for Scenes A and C also support the hypothesis that there are more fixations when advertisements are introduced in a scene. The assumption that these extra fixations will fall on the advertisements is only partially confirmed. For all three scenes there are nearly no fixations on the one advertisement in Condition 1. In Condition 3 there are considerable numbers of fixations on the advertisements; the effect is again stronger for Scenes A and C. About half of the additional fixations for Scene A in Condition 3 compared with Condition 0 fall on advertisements. For Scene C this is the case for almost all additional fixations. The systematic increase in search time and number of fixations for Scenes A and C suggests that introducing advertisements in a scene mainly results in a less efficient scanning of the scene. The increase in search time when advertisements are introduced only partly consists of the time spent actually fixating advertisemerits. As to Scene B, a fully satisfactory explanation for the absence of the predicted effects cannot be given. Two points that might explain the results can be mentioned, however. First, inspection of the scene slides shows that the routing sign in Scene B is in a more central position than the signs in Scenes A and C. The second point concerns the scan paths
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Scene A
Scene B
272
Three advertisement areas
December 1989
of the subjects. The eye-movement recordings indicate that in each scene there is a point which attracts the fLxation after the first saccade of almost every subject. In Scenes A and C the position of this point is such that the scan path, which always starts at the position from which the fLxation cross has just disappeared, is diverted from the routing sign, while in Scene B this point is close to the routing sign. Once the eye fixates at a short distance from the sign, as in Scene B, distraction by advertisements might become unlikely. In conclusion, itshould be stressed that the increase in search time and in the number of fixations found for Scenes A and C is a relevant and substantial phenomenon for two reasons. Firstly, the advertisements inserted in the scenes are unusually small compared with normal practice. Secondly, the effects appear even though the subjects are cued to search for white-on-blue routing signs. Apparently, the search conspicuity (Cole and Hughes, 1984) of routing signs induced by the set of the subjects cannot compensate for the attention conspicuity of even small advertisements. As to the procedure used, it can be concluded that by using eye-movement recording, the objectivity problems of the locating performance score described by Boersema and Zwaga (1985) can be avoided. Search time derived from the eye-movement data appears to be a sensitive measure of the conspicuity of routing information in realistic scenes. Moreover, the eye-movement data provide additional insight into the phenomena underlying conspicuity.
References
Boersema, T., and Zwaga, H.J.G. 1985, Applied Ergonomics, 16.4,267-273. The influence of advertisements on the conspicuity of routing information. Cole, B.L., and Hughes, P.K. 1984, Human Factors, 26, 299-313. A field trial of attention and: search conspicuity. Cole, B.L., and Jenkins, S.E. 1984, Vision Res, 24, 261 270. The effect of variability of background elements on the conspicuity of objects.
Dewar, R.E., Ells, J.G., and Mundy, G. 1976, Human 392. Reaction time as an index of traffic sign perception.
Jenkins, S.E., and Cole, B.L. 1982, Vision Res, 22, 1241 1252. The effect of the density of background elements on the conspicuity of objects.
Dewar, R.E., Ells, J.G., and Cooper, P.J. 1977, Transportation Engng, 47.6, 19-23. Evaluation of roadway guide signs at a large airport.
Kr6se, B.J.A. 1986, A description of visual structure. Kanters, Alblasserdam.
Factors, 18,381
Francolini, C.M., and Egeth, H.E. 1979, Perception & Psychophvsics, 25, 99-110. Perceptual selectivity is task
Meddis, R. 1984, Statistics using ranks. A unified approach. Basil Blackwell, New York.
dependent: the pop-out effect poops out.
Shoptaugh, C.F., and Whitaker, L.A. 1984, Human Factors, 2 6 , 2 3 5 - 2 4 4 . Verbal response times to directional traffic signs embedded in photographic street scenes.
Gordon, D.A. 1981, Human Factors, 23, 453-466. The assessment of guide sign information load.
Smith, S.L. 1962, J Exper Psychol, 64, 434-440. Colour coding and visual search.
Green, B.F., and Anderson, L.K. 1956, J Exper Psychol, 51, 19 24. Colour coding in a visual search task.
Treisman, A.M., and Gelade, G. 1980, Cognitive Psychol, 12, 97-136. A feature integration theory of attention.
Holahan, C.J., Culler, R.E., and Wilcox, B.L. 1978, Human Factors, 2 0 , 4 0 9 - 4 1 3 . Effects of visual distraction on
Williams, L.G. 1966, Perception & Psychophysics, 1, 315318. The effect of target specification on objects fixated during visual search.
reaction time in a simulated traffic environment.
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/j
273
Conspicuity in realistic scenes: an e y e - m o v e m e n t measure T. Boersema*, H.J.G. Zwaga t and A.S. Adams** *Department of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands tDepartment of Social Sciences, University of Utrecht, The Netherlands **School of Psychology, University of New South Wales, Australia An experiment is described to measure the distracting effects of advertisements on the conspicuity of routing signs in realistic scenes. Slides of railway station scenes were shown in which subjects had to search for a target word used in a routing sign present in the scene. Eye movements were recorded to determine search time and number of fixations during search time. Both search time and number of fixations increased systematically with the number of advertisements in two of the three experimental scenes. The distribution of fixations over the scenes is discussed. Keywords: Eye movement, route information, signs, conspicuity
Introduction In the presentation of routing information such as is found in airport terminals, railway stations and shopping centres, many questions remain unanswered concerning practical methods of ensuring the conspicuity of that information. The relative conspicuity of an object in this situation can be operationally defined in terms of the probability that the object will be noticed by an observer within a fixed time or, conversely, in terms of the time required to locate the object. While conspicuity is determined by many properties of the object itself, and by the cognitive state of the observer, the question addressed here concerns the distracting effect of surrounding advertisements, which themselves are, of course, designed to be conspicuous. Early laboratory work on searching for targets in cluttered visual fields showed that giving information about the physical properties of a target greatly assisted a search task (Green and Anderson, 1956; Smith, 1962; Williams, 1966). More recent studies led to the conclusion that the greater the degree of physical difference between target and background items, the smaller the slope of the curve relating detection time to number of background items (Francolini and Egeth, 1979; Treisman and Gelade, 1980). Kr6se (1986) showed that a positive correlation existed between the detectability of a target and the structure dissimilarity between target and background items. In examining separate dimensions in detail, Jenkins and Cole (1982) found that background density of a field of discs affected a contrast detection task but not a size one, while Cole and Jenkins (1984) found that variability of size of the same background discs affected a size detection task but not a contrast one. Yreisman and Gelade (1980) showed that, when a simple detection operation was required, the colour dimension was particularly potent in making a target impervious to the effects of background details. Other studieg have examined these effects in practical contexts. Holahan et al (1978), in a laboratory examination of the effect of distractions around a stop sign, found that
the number, colour and proximity of distractors all had an effect on the reaction time to the sign. Shoptaugh and Whitaker (1984) found that directional traffic signs embedded in photographed street scenes were responded to more slowly when they were embedded in scenes which were rated as being more complex. Cole and Hughes (1984) introduced the concepts of search conspicuity and attention conspicuity in a field study of target visibility. Search conspicuity is the property enabling a target to be seen when it is the object of specific search, whereas attention conspicuity enables an object to be seen when it is unexpected. In their study, subjects drove through streets reporting either specific planted targets, in which case the targets required search conspicuity, or all objects, including these targets, in which case the targets required attention conspicuity. It was found that objects were located least often in the clutter of shopping areas, more often in arterial road sections, and most often in residential road sections. With respect to freeway routing signs, Gordon (1981) found that photographs of such overhead signs were not responded to any more quickly when adjacent irrelevant signs were removed. However, the signs used in Gordon's study were such that their location was highly predictable. Furthermore, the distracting information was, in four out of five signs, in the periphery of the bank of signs to which subjects were attending, and would therefore not be expected to interfere with the task. When searching for routing information in public situations the target location is, of course, not known. In addition, in such situations it is not unusual for advertising signs to be mixed with relevant routing signs. A further complication might be that users new to the environment do not know the shape and the colour of the routing signs. Also, they do not know the precise nature of the routing information (e g, a word, a phrase or a symbol). It is difficult to argue that, in a situation where a user does not know the location, the shape and the colour of the routing signs, nor the nature of the information needed, task performance depends on search conspicuity only. In those circumstances
0003-6870/89/04 0267-07 ~;03.00 © 1989 Butterworth & Co (Publishers) Ltd
Applied Ergonomics
December 1989
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considerable attention conspicuity will be required, at least from the routing signs themselves. To a certain extent search conspicuity will also play a role because users have general expectations about routing systems based on prior experience. Taking these aspects into account, the answer to the practical question as to whether advertisements commonly found in the vicinity of routing signs seriously disrupt the search process cannot be readily predicted from the studies described above. Studying directly the effect of the presence of advertisements on the conspicuity of routing information, Boersema and Zwaga (1985) used slides of railway station scenes containing varying numbers of advertisements of different sizes. Exposure time of the scene slides was one second. The subject's task was tO report the presence of white-on-blue routing signs and then to report each sign's location. These locations had to be indicated on a grid of 24 numbered squares projected after each scene slide. The results of experiment showed that the introduction of only one advertisement in a scene had a greater effect than the further introduction of a second and a third advertisement. The results also indicated that larger advertisements had a greater effect than smaller advertisements. Scoring problems arose when subjects did not correctly identify the grid position for a sign. In those cases a laborious procedure was required in order to keep the objectivity of the scoring at an acceptable level. To avoid these problems and yet maintain the essence of the subject's task (searching for routing information in a realistic scene), the use of reaction time seemed a promising approach. Dewar et al (1976) demonstrated a high correlation between a laboratory measure of reaction time to identify and classify signs and a field measure of legibility. In another study, Dewar et al (1977) showed that laboratory measures of the time required to interpret road direction signs was positively related to data from field traffic flow and driver interview measures. Prior to the experiment reported here, a series of pilot experiments has been conducted by us in which reaction time was used as a performance measure. In these experiments, a slide containing a single-word destination and subsequently a slide showing a scene in a public building were presented to the subjects. They then had to press a button as soon as they had found the sign with the destination in the scene slide. Pressing the button made the slide disappear, and, as a check, the subject had to report the orientation of the arrow associated with the destination (left, ahead or right). Using the same photographic technique as in our previous study (Boersema and Zwaga, 1985), the number of advertisements in three of the scenes shown to the subjects was varied systematically. It was expected that reaction time for a scene (i e, the time needed to find the destination specified, to identify the orientation of the arrow, and to press the button) would increase with the number of advertisements in that scene. However, the reaction time was not systematically related to the number of advertisements in a scene. It can be argued that, in an experiment as has just been described, the reaction time consists of two parts: the time a subject needs to find the routing sign with the target destination (search time) and the time used for reading this routing sign and deciding on the response (processing time). For the purposes of the present investigation into conspicuity,it is only the first of these times which is required. A
268
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method which eliminates the second of these measures would theretore be preferable as it would remove an unnecessary source of error variance. The use of eye-movement measurement is one such method and is feasible in this case as the times recorded in the reaction time experiment (between one and three seconds) were such that several eye movements would have been executed. An experiment is reported here in which reaction time is divided into search time and processing time by means of eye-movement recording. Subjects have to search for specific destinations in realistic scenes containing varying numbers of advertisements. It is hypothesised that search time will increase systematically with the number of advertisements, even if they are evidently distinct from routing signs, and that processing time and total reaction time will not change significantly. In essence, it can be assumed that the expected increase in search time is the direct effect of changes in the scan path of the subjects resulting from the introduction of advertisements in a scene. This assumption is supported by Kr6se's (1986) eye-movement experiment in which he measured the effect of strong and weak distractors on the locating performance tbr a target. His results showed that the presence of distractors in the visual field increased the number of fixations necessary to locate the target. These extra fixations were located on, or in the direction of, the distractors. It is therefore hypothesised that the introduction of advertisements will increase the number of fixations during search time, with the extra fixations being on the advertisements.
Method Subjects Subjects were 54 undergraduates and staff of the Delft department, aged between 18 and 43 years. All subjects had at least normal, uncorrected vision. The students were paid for their participation.
Stimulus material In the experiment, a total of 15 colour slides showing scenes in railway stations and other public environments were used as stimulus material. All scenes contained routing signs with white lettering on a blue rectangle. Six of the slides were filler slides and showed randomly chosen scenes containing advertisements as welt as routing information. The other nine slides were experimental slides. They were based on original slides from three different scenes (Experimental Scenes A, B and C). From each of these original slides, using photographic techniques, three experimental slides were constructed, containing either zero, one or three advertisements. The advertisements were selected from those encountered in public environments. All advertisements were rectangular, and none contained the routing sign colour of blue. Fig. 1 shows prints of the three experimental slides from Scene A. The scene in Fig. 1 is representative of the other experimental scenes with regard to complexity, transparency, crowdedness, etc. In the experimental scenes, the advertisements were two to three times the size of a routing sign, which is smaller than advertisements normally encountered in those circumstances. In general, the arrangements of routing signs and advertisements in Scenes A, B and C were comparable.
=
E
o~
=
(a)
~;i~i~ ~ <<~
(b) Fig. 1
The three experimental slides from Scene A with zero (a), one (b), and three (c, overleaf) advertisements (see also the front cover for Figs. la and lc)
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December 1989
269
(c) In addition to the scene slides, there were 10 other slides: one with a fixation cross and nine slides each with a singleword destination, one for each scene.
tended visual angles between 6.3 ° and 11.7 ° (horizontally) and between 2-6 ° and 6-3 ° (vertically).
Oesign Apparatus Two Kodak Carousel slide projectors, controlled by a PDP 11/73 minicomputer, were used: one to present the fixation cross slide, the other to present the text slides and the associated scene slides. The computer also measured the reaction times. Eye movements were recorded with an eye marker (Demel Debie 84) using the corneal reflection bright pupil technique, The subjects were not allowed to make head movements. The accuracy o f the measurements was one degree; sampling frequency was 50 Hz.
Projection conditions The size of the projected scenes and the distance between subject and projection screen were chosen such that the visual angle of objects in the projected scene was the same as in the actual scene. This means that the subjects in the experiment perceived the projected scene as if they stood in the position o f the camera in the actual scene. Given the picture angle o f the camera lens used, this required that projection width and viewing distance were the same (in the experiment: 200 era; projection height was 132 cmo). Thus, the projected scenes subtended visual angles of 53.1 (horizontally) and 36-5 ° (vertically). The visual angles of the routing signs in the experimental scenes varied between 5-2 ° and 6"9° (horizontally) and between 2 ~9° and 2"9 ° (vertically). The advertisements sub-
270
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December 1989
There were three experimental conditions, one for each number of advertisements in the experimental scenes (zero, one or three). Subjects were randomly assigned to three groups o f 18 with each group assigned to one condition. The between-group manipulation was therefore the number of distracting advertisements. The series of filler slides was shown to all subjects in the same order. Depending on the condition, appropriate experimental slides were inserted, with a fixed position for each experimental scene.
Procedure and experimental design Each subject was presented with a total o f nine trials, of which three were the experbnental trials. The nine trials were preceded by six practice trials. Also, for the practice trials, slides showing scenes in public environments were used. Each trial consisted of a sequential presentation o f three slides: a target destination slide, a slide with a fixation cross. and a scene slide. The trial began with the subject pressing a button to start the projection of the target destination, which the subject was instructed to read aloud. This destination was the word to be searched for in the following scene slide. The subject then pressed the button again, and the destination was replaced with a fixation cross, which was followed automatically two seconds later with the scene slide. The subject was instructed to find as quickly as possible both the target destination and its associated
arrow in the scene's routing information, then to press the button to terminate the presentation of the scene slide, and finally to report verbally the direction of the arrow.
depending on condition and scene. In the other cases the eye movement data were incomplete and had to be discarded.
Prior to the analysis of the data from the experimental scenes, the results from the filler scenes for the three independent groups were compared. These data showed no significant differences between the groups on any of the four dependent variables: search time, processing time, reaction time and number of fixations. Subjects made no mistakes reporting the arrow directions.
The results of Scenes A, B and C are presented in Table 1. In this table median times and numbers are given in order to convey an impression of the absolute level of the measurements. The calculations for Meddis's tests, however, are based on mean ranks, so the sometimes minimal differences between medians can be misleading when interpreting the meaning of those differences. Analysis of the time data shows that in Scenes A and C, search times increase systematically with the number of advertisements (0 < 1 < 3, test for trends), while processing times as well as reaction times remain constant (non-specific test). In Scene B there is not only, as for the two other scenes, no effect of advertise ments on processing time and reaction time, but there is also no effect on search time (non-specific test). Analysis of the fixation data shows that in Scenes A and C the number of fixations increases systematically with the number of advertisements (0 < 1 < 3, test for trends). In Scene B there is no effect of advertisements on the number of fixations (nonspecific test).
For each of the three experimental scenes, results and statistical analyses are presented separately because of the uncontrolled qualitative differences between the scenes. The data are analysed using the non-parametric technique developed by Meddis (1984). Meddis's specific test for trends is used to test if search time and number of fixations increase systematically with the number of advertisements. Meddis's non-specific test is used where no direction of an effect was predicted (processing time and reaction time). Complete data were collected from 1 2 - 1 6 subjects,
In order to test the hypothesis that the extra fixations will fall on advertisements, the number of fixations on the advertisements are compared with the number of fixations on the corresponding areas of the scenes ~-here no advertisements are inserted (Table 2). In Condition 1 there is only one fixation on the advertisement (Scene C), and none on the corresponding areas in Condition 0. The numbers of fixations on advertisements in Condition 3 are substantial, whereas the numbers of fixations on the corresponding areas in Condition 0 are again minimal.
Eye movements of the left eye and reaction times were recorded. Search time was operationally defined as the time from the start of the presentation of a scene slide until the beginning of the first fixation on the routing sign. Processing time was the difference between reaction time and search time. Fixations were defined using simultaneously two criteria: one for the duration (at least 60 ms) and one for the maximum acceptable displacement of the line of sight.
Results
Table 1: Median search times (st), processing times (pt) and reaction times (rt)
in seconds and median numbers of fixations during search time (fix) for Scenes A, B and C under Conditions 0, 1 and 3. The numbers of subjects with complete data (n) and the statistical test results are indicated n
st
pt
rt
fix
12 15 14
0"570 0'860 1 '025 Z=2"486 p<0'01
1 "535 1 '500 1 '355 H=0"110 p>0"10
2"005 2"290 2"625 H=4'252 p>0"10
20 3 "0 4"0 Z=3"768 p<0'01
16
0"505
0"820
1 "315
2"0
1
14
0"495
0"955
1 "465
20
3 Key statistic
15
0"570 H=0"300
0"810 H=0"766
1 "390 H=0"182
2"0 H=0"590
p>0"10
p>0"10
p>0"10
p>0'10
16 15
0"530 0"700
1 "520 1 '610
2"225 2"310
2"0 3"0
15
0"710 Z=3"403 p<0'01
2'300 H=2"924 p>0"10
3"020 H=4-458 p>010
3"0 Z=2-384 p <0"01
Scene A Condition 0 1 3 Key statistic
Scene B Condition 0
Scene C Condition 0 1 3 Key statistic
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271
Table 2: Numbers of fixations during the search for Scenes A, B and C on the advertisement under Condition 1 and on the corresponding area under Condition 0 and on the three advertisements under Condition 3 and on the three corresponding areas under Condition 0
One advertisement area Total
Mean per subject
Condition 0
0
0'00
Condition 0
1
0"08
1
0
0'00
3
16
1 "14
Condition 0
0
0"00
Condition0
1
0"06
1
0
0"00
3
5
0"33
Condition 0
0
0"00
Condition 0
0
0"00
1
1
0"07
3
14
0"93
Scene A
Mean per subject
Scene B
Scene C
Scene C
A further exploratory analysis of the data with regard to the duration of fixations and the length of saccades shows no systematic effects. Discussion
The results of the experiment show that the presence of advertisements in an environment can decrease the efficiency with which information can be found. Search time for relevant information increases due to the increase in the number of fixations during search. The analyses of the search time data for Scenes A and C confirm the hypothesis that search time increases systematically with the number of advertisements. The hypothesis that processing time and reaction time will not change is confirmed for all three experimental scenes. The results for Scenes A and C also support the hypothesis that there are more fixations when advertisements are introduced in a scene. The assumption that these extra fixations will fall on the advertisements is only partially confirmed. For all three scenes there are nearly no fixations on the one advertisement in Condition 1. In Condition 3 there are considerable numbers of fixations on the advertisements; the effect is again stronger for Scenes A and C. About half of the additional fixations for Scene A in Condition 3 compared with Condition 0 fall on advertisements. For Scene C this is the case for almost all additional fixations. The systematic increase in search time and number of fixations for Scenes A and C suggests that introducing advertisements in a scene mainly results in a less efficient scanning of the scene. The increase in search time when advertisements are introduced only partly consists of the time spent actually fixating advertisemerits. As to Scene B, a fully satisfactory explanation for the absence of the predicted effects cannot be given. Two points that might explain the results can be mentioned, however. First, inspection of the scene slides shows that the routing sign in Scene B is in a more central position than the signs in Scenes A and C. The second point concerns the scan paths
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Scene A
Scene B
272
Three advertisement areas
December 1989
of the subjects. The eye-movement recordings indicate that in each scene there is a point which attracts the fLxation after the first saccade of almost every subject. In Scenes A and C the position of this point is such that the scan path, which always starts at the position from which the fLxation cross has just disappeared, is diverted from the routing sign, while in Scene B this point is close to the routing sign. Once the eye fixates at a short distance from the sign, as in Scene B, distraction by advertisements might become unlikely. In conclusion, itshould be stressed that the increase in search time and in the number of fixations found for Scenes A and C is a relevant and substantial phenomenon for two reasons. Firstly, the advertisements inserted in the scenes are unusually small compared with normal practice. Secondly, the effects appear even though the subjects are cued to search for white-on-blue routing signs. Apparently, the search conspicuity (Cole and Hughes, 1984) of routing signs induced by the set of the subjects cannot compensate for the attention conspicuity of even small advertisements. As to the procedure used, it can be concluded that by using eye-movement recording, the objectivity problems of the locating performance score described by Boersema and Zwaga (1985) can be avoided. Search time derived from the eye-movement data appears to be a sensitive measure of the conspicuity of routing information in realistic scenes. Moreover, the eye-movement data provide additional insight into the phenomena underlying conspicuity.
References
Boersema, T., and Zwaga, H.J.G. 1985, Applied Ergonomics, 16.4,267-273. The influence of advertisements on the conspicuity of routing information. Cole, B.L., and Hughes, P.K. 1984, Human Factors, 26, 299-313. A field trial of attention and: search conspicuity. Cole, B.L., and Jenkins, S.E. 1984, Vision Res, 24, 261 270. The effect of variability of background elements on the conspicuity of objects.
Dewar, R.E., Ells, J.G., and Mundy, G. 1976, Human 392. Reaction time as an index of traffic sign perception.
Jenkins, S.E., and Cole, B.L. 1982, Vision Res, 22, 1241 1252. The effect of the density of background elements on the conspicuity of objects.
Dewar, R.E., Ells, J.G., and Cooper, P.J. 1977, Transportation Engng, 47.6, 19-23. Evaluation of roadway guide signs at a large airport.
Kr6se, B.J.A. 1986, A description of visual structure. Kanters, Alblasserdam.
Factors, 18,381
Francolini, C.M., and Egeth, H.E. 1979, Perception & Psychophvsics, 25, 99-110. Perceptual selectivity is task
Meddis, R. 1984, Statistics using ranks. A unified approach. Basil Blackwell, New York.
dependent: the pop-out effect poops out.
Shoptaugh, C.F., and Whitaker, L.A. 1984, Human Factors, 2 6 , 2 3 5 - 2 4 4 . Verbal response times to directional traffic signs embedded in photographic street scenes.
Gordon, D.A. 1981, Human Factors, 23, 453-466. The assessment of guide sign information load.
Smith, S.L. 1962, J Exper Psychol, 64, 434-440. Colour coding and visual search.
Green, B.F., and Anderson, L.K. 1956, J Exper Psychol, 51, 19 24. Colour coding in a visual search task.
Treisman, A.M., and Gelade, G. 1980, Cognitive Psychol, 12, 97-136. A feature integration theory of attention.
Holahan, C.J., Culler, R.E., and Wilcox, B.L. 1978, Human Factors, 2 0 , 4 0 9 - 4 1 3 . Effects of visual distraction on
Williams, L.G. 1966, Perception & Psychophysics, 1, 315318. The effect of target specification on objects fixated during visual search.
reaction time in a simulated traffic environment.
\ A unique work addressing interaction between Health and Safety and Ergonomics
HEALTH, SAFETY AND ERGONOMICS A S Nicholson and J E Ridd This book provides a discussion of the direct and important part ergonomics plays in the prevention of occupational ill-health and accidental injury at work, and its use as an aid to management decision-making on the design, construction and operation of plant and equipment, and in the preparation of work systems such that when commissioned, these systems and apparatus will function more efficiently. It also demonstrates that the quest for improving levels of occupational health and safety, utilising ergonomic principles, can bring wider benefits by maximising performance, comfort and worker morale. October 1988
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