Dela Cruz Jaydrell

I. INTRODUCTION Visual search is a type of perceptual task requiring attention. Visual search involves an active scan of the visual environment for a particular object or feature the target among other objects or features the distracters. Visual search can take place either with or without eye movements. Common examples include trying to locate a certain brand of cereal at the grocery store or a friend in a crowd . The scientific study of visual search typically makes use of simple, well-defined search items such as oriented bars or colored letters. (Treisman & Gelade, 1980) The efficiency of visual search depends on the number and type of distracters that may be present. Search tends to be more efficient when the target is very different from the distracters. The number of targets and distractors in a given visual array is called the display size. The display size effect is the degree to which task performance Reaction time and/or accuracy depends on the display size. The magnitude of the display size effect can vary greatly, from effectively zero. In searches for a red target among green distracters, called a feature search to a large effect. In searches for a red X among green Xs and red Os, called a conjunction search. Search tasks with a small display size effect are referred to as "efficient;" search tasks showing a large display size effect are termed "inefficient." The feature integration theory, developed by Treisman and Gelade since the early 1980s has been one of the most influential psychological models of human visual attention. According to Treisman, in a first step to visual processing, several primary visual features are processed and represented with separate feature maps that are later

integrated in a saliency map that can be accessed in order to direct attention to the most conspicuous areas. Treisman distinguishes two kinds of visual search tasks, feature search and conjunction search. Feature search can be performed fast and pre-attentively for targets defined by primitive features. Conjunction search is the serial search for targets defined by a conjunction of primitive features. It is much slower and requires conscious attention. She concluded from many experiments that color, orientation, and intensity are primitive features, for which feature search can be performed. The visual search task has become one of the most widely used measures in the study of visual perception and attention, beginning with the work of Treisman and Gelade. Most of this work has aimed to characterize visual attention limitations by scrutinizing “search slopes”. In speeded visual search tasks in which an observer has an opportunity to view a display as long as s/he would like, arranged so that the target differs from uniform distractors in only one feature dimension, search time usually does not increase with the number of distractors. In daily life, we experience essentially the same phenomenon from time totime, as when we find a person wearing red in a large crowd of people all wearing green. This “pop-out” effect is generally agreed to reflect spatially parallel processing When the target/distractor difference is very subtle, however, even this sort of singleton search often shows a substantial display-set-size effect. Thus, a person wearing red cannot be so readily picked out from a crowd of people all wearing slightly pinkish red chartreuse. Thus, “difficulty” (in the sense of target–distractor similarity) significantly

affects the efficiency (slope) of a visual search. A number of researchers have concluded that target– distractor similarity is critical in determining the attentional limitations evident in visual search). What is not yet clear, however, is what causes the inefficiency in singleton searches involving a subtle feature difference. One possibility is that the inefficiency reflects an attentional capacity limit, a concept that will be discussed in more depth below. Another possibility is that as the processing of each item is impaired, a display-set-size effect arises for reasons other than attentional capacity limitation. Attentional capacity limits and the serial/parallel dichotomy The highly influential Feature Integration Theory of Treisman and Gelade argues that whereas feature singleton search is accomplished with parallel processing, search requiring detection of targets defined in a more complex fashion (e.g. by feature conjunction) requires serial processing. This theory stimulated a great deal of research. However, most researchers have abandoned it, as evidence accumulated to suggest that conjunction search can sometimes be quite efficient and that (as mentioned above), feature search can be inefficient when targets and distracters are very similar). In addition, as is well known, sizable display set size slopes might be predicted by either a serial search or a limitedcapacity parallel search in which processing is always parallel, but worsens when display set size increases (Townsend, 1976, 1990; Wolfe, 1998a).

II. OBJECTIVE This experiment intends to identify the features is a visual search task in which subjects are asked to detect the presence of one or more target items among a set of distracter item. The experiment searchers presented from 1-30 letters on each trial and examined how the number of letter in display affected the time it look subjects to detect the presence of a target item. The subject to detect a capital letter T in a display containing either Ys and Is or Zs and Is. ( see Figure 4A)

III. THEORETICAL STANDPOINT Visual search is an excellent paradigm for studying how recognition takes place and what features or aspects of an object are used in recognition. For example, theories of object perception have been tested with visual search studies. Anne Treisman used visual search as one source of evidence for her theory that attention serves to integrate features into a whole perception of an object. Visual search has also been used to evaluate theories of attention. Visual search is also a convenient paradigm for looking for effects of practice in strictly visual analysis, and the concept of automaticity, which develops with practice, was first developed in a visual search paradigm. (et.al Anne Treisman 1990) Most visual search paradigms present a display that has a single target in it. The number of nontargets (distracters) is varied to allow the rate of search to be calculated. In Figure 1 below, the search functions show the change in search time as the number of distracters is varied. Linear functions are plotted here under the assumption – not always true -- that each additional nontarget in the array adds a constant increment to the search time. The search time in the upper function is 12 msec per added item (the search time

difference between 5 and 30 items is 300 msec in the figure). However, we assume that the number of nontargets searched through is, on the average, half of the total number of nontargets in the array. This results in a search rate of 24 msec/item. The lower function gives a search rate of 8 msec per item by the same calculation. (et.al Anne Treisman 1990) Note that the search rate is the speed with which nontargets are rejected. (The time to accept a target is not directly measured.) The search rate is therefore influenced strongly by the nature of the nontargets and their similarity to the target. Looking for a rounded letter like “e” among rounded letters takes longer than looking for an angular letter like “x.” In the two cases, one is searching through the same set of rounded letters, but the search rate varies with the target. Why? One hypothesis is that visual search is a process of feature detection and discrimination. It is more difficult to reject nontargets that have the same features as the target, possibly because the features of the nontargets trigger close examination of them and (2) once attended the nontargets need to be discriminated from targets. (et.al Anne Treisman 1990)

REFERENCES •

Wolfe, J M (1998). Visual Search. In H. Pashler (Ed.), Attention, East Sussex, UK: Psychology Press.

•

Theeuwes, J. (1992). Perceptual selectivity for color and form. Perception & Psychophysics, 51, 599-606.

•

Treisman, A., & Gelade, G., 1980. A feature integration theory of attention. Cognitive Psychology, 12, 97-136.

•

Verghese, P. (2001). Visual search and attention: A signal detection theory approach. Neuron, 31, 523-535(13).

Acknowledgement: I would like to thanks to my beloved professor Mr. Reynold Varela for helping, supporting and guiding to my research paper. And also the Adamson University Band who helping and participates to this experiment. And I would like thanks to my classmate who always helping me to finished this research paper.

V. LIMITATION OF THE EXPERIMENT When a visual search task is very difficult (as when a small feature difference defines the target), even detection of a unique element may be substantially slowed by increases in display set size. This has been attributed to the influence of attentional capacity limits. We examined the influence of attentional capacity limits on three kinds of search task: difficult feature search (with a subtle featured difference), difficult conjunction search, and spatial-configuration search. In all 3 tasks, each trial contained sixteen items, divided into two eight-item sets. The two sets were presented either successively or simultaneously. Comparison of accuracy in successive versus simultaneous presentations revealed that attentional capacity limitations are present only in the case of spatial-configuration search. While the other two types of task were inefficient (as reflected in steep search slopes), no capacity limitations were evident. We conclude that the difficulty of a visual search task affects search efficiency but does not necessarily introduce attentional capacity limits.

VI. HYPOTHESIS 1. There is a significant difference in time required to search through condition 1 and condition 3. 2. There is a significant difference smaller or larger than the difference between searching through condition 2 and 4. 3. There is a similarity of features between letters I and Z versus letter T as compared to the similarity of features between letters Y and I versus the letter T.

VII. METHODOLOGY A total of 30 first to forth year college student at the Adamson University. Female 15 and Male 15 age of 16 to 25 years old.

VIII. PROCEDURE You can demonstrate the effects of the type and number of distracters on people’s ability to locate the target items using the displays in figure 4A. To complete this demonstration you will need several volunteers and a watch that will allow you to time in seconds. In this experiment, volunteers will search through four displays in each of four conditions. You will test all participants in manner described below. After testing is completed, compute the average search time for each of the conditions. Tell participants theirs task is to search for the capital letter T in a series of displays, each containing one T among a number of other distracter letters. There are four different conditions, and participants should search through each display in each condition are quickly as possible until they find the target T. (Use sheets of paper to cover up the three conditions not being searched.) Ask the participants to continue searching until they have gone through all four displays for a particular condition and say, “ Done” when they are finished. Record how long it takes each person to complete the search.

IV. Research Paradigm COGNITIVE PROCESS

MEMORY

TOPDOWN PROCES SES

KNOWLEDGE

LANGUEGE

IDENTIFICATION/RECOGNITION

ANALYSIS OF COMPONENTS PERCEPTION

VSUAL FEATURES SENSATION BOTTO M-UP PROCES SES

SENSORY PROCESSES

OBJECTS / TEXTURE